Cardiac activation sequence monitoring and tracking

ABSTRACT

Cardiac monitoring and/or stimulation methods and systems provide monitoring, diagnosis, and defibrillation and/or pacing therapies. A signal processor receives a plurality of composite signals associated with a plurality of sources, performs a source separation, and produces one or more cardiac signal vectors associated with all or a portion of one or more cardiac activation sequences based on the source separation. A method of signal separation involves detecting a change in a characteristic of the cardiac signal vector relative to a baseline. One or more vectors and/or activation sequences may be selected, and information associated with the vectors and/or activation sequences may be stored and tracked.

RELATED PATENT DOCUMENTS

This application is a continuation of U.S. patent application Ser. No.10/955,397 filed on Sep. 30, 2004, to issue as U.S. Pat. No. 7,890,159on Feb. 15, 2011, to which Applicant claims priority under 35 U.S.C.§120, and which is incorporated herein by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates generally to implantable medical devicesemploying cardiac signal separation and, more particularly, to cardiacsensing and/or stimulation devices employing cardiac activation sequencemonitoring and tracking.

BACKGROUND

The healthy heart produces regular, synchronized contractions. Rhythmiccontractions of the heart are normally initiated by the sinoatrial (SA)node, which is a group of specialized cells located in the upper rightatrium. The SA node is the normal pacemaker of the heart, typicallyinitiating 60-100 heartbeats per minute. When the SA node is pacing theheart normally, the heart is said to be in normal sinus rhythm.

If the heart's electrical activity becomes uncoordinated or irregular,the heart is denoted to be arrhythmic. Cardiac arrhythmia impairscardiac efficiency and may be a potential life-threatening event.Cardiac arrhythmias have a number of etiological sources, includingtissue damage due to myocardial infarction, infection, or degradation ofthe heart's ability to generate or synchronize the electrical impulsesthat coordinate contractions.

Bradycardia occurs when the heart rhythm is too slow. This condition maybe caused, for example, by impaired function of the SA node, denotedsick sinus syndrome, or by delayed propagation or blockage of theelectrical impulse between the atria and ventricles. Bradycardiaproduces a heart rate that is too slow to maintain adequate circulation.

When the heart rate is too rapid, the condition is denoted tachycardia.Tachycardia may have its origin in either the atria or the ventricles.Tachycardias occurring in the atria of the heart, for example, includeatrial fibrillation and atrial flutter. Both conditions arecharacterized by rapid contractions of the atria. Besides beinghemodynamically inefficient, the rapid contractions of the atria mayalso adversely affect the ventricular rate.

Ventricular tachycardia occurs, for example, when electrical activityarises in the ventricular myocardium at a rate more rapid than thenormal sinus rhythm. Ventricular tachycardia may quickly degenerate intoventricular fibrillation. Ventricular fibrillation is a conditiondenoted by extremely rapid, uncoordinated electrical activity within theventricular tissue. The rapid and erratic excitation of the ventriculartissue prevents synchronized contractions and impairs the heart'sability to effectively pump blood to the body, which is a fatalcondition unless the heart is returned to sinus rhythm within a fewminutes.

Implantable cardiac rhythm management systems have been used as aneffective treatment for patients with serious arrhythmias, as well asfor patients with conditions such as heart failure. These systemstypically include one or more leads and circuitry to sense signals fromone or more interior and/or exterior surfaces of the heart. Such systemsalso include circuitry for generating electrical pulses that are appliedto cardiac tissue at one or more interior and/or exterior surfaces ofthe heart. For example, leads extending into the patient's heart areconnected to electrodes that contact the myocardium for sensing theheart's electrical signals and for delivering pulses to the heart inaccordance with various therapies for treating arrhythmias.

Typical implantable cardioverter/defibrillators include one or moreendocardial leads to which at least one defibrillation electrode isconnected. Such implantable cardioverter/defibrillators are capable ofdelivering high-energy shocks to the heart, interrupting the ventriculartachyarrhythmia or ventricular fibrillation, and allowing the heart toresume normal sinus rhythm. Implantable cardioverter/defibrillators mayalso include pacing functionality.

SUMMARY

The present invention is directed to cardiac monitoring and/orstimulation methods and systems that provide monitoring, diagnosing,defibrillation therapies, pacing therapies, or a combination of thesecapabilities. Embodiments of the present invention relate generally toimplantable medical devices employing cardiac signal separation and,more particularly, to cardiac monitoring and/or stimulation devicesemploying automated cardiac activation sequence monitoring and/ortracking.

Embodiments of the invention are directed to devices having a signalprocessor that receives two or more composite signals associated withtwo or more sources, performs a source separation, and produces one ormore cardiac signal vectors associated with all or a portion of one ormore cardiac activation sequences based on the source separation. One orboth of performing the source separation and producing the cardiacsignal vectors may be patient-internal or patient-external operations.

A change may be detected in a characteristic of the cardiac signalvectors relative to a baseline, such as established by an initial sourceseparation and/or clinical information. The change may be detected usinga subsequent source separation. The change detected may involve one ormore of: an angle change of one or more cardiac signal vectors; amagnitude change of one or more cardiac signal vectors; a variancechange of one or more cardiac signal vectors; a power spectral densitychange of the angle of one or more cardiac signal vectors; a powerspectral density change of the magnitude of one or more cardiac signalvectors; a trajectory change of one or more cardiac signal vectors; atemporal profile change of one or more cardiac signal vectors; a rate ofchange of angle of one or more cardiac signal vectors; a rate of changeof magnitude of one or more cardiac signal vectors; a rate of change ofvariance of one or more cardiac signal vectors; a rate of change oftemporal profile of one or more cardiac signal vectors; a trend of theangle of one or more cardiac signal vectors; a trend of the magnitude ofone or more cardiac signal vectors; a trend of the variance of one ormore cardiac signal vectors; and a trend of the temporal profile of oneor more cardiac signal vectors.

The change may be detected beat-to-beat, within a cardiac cycle, over apredetermined time period, over two or more cardiac cycles, at apre-determined time, upon the reception of an external stimulus, andupon the reception of a patient-activated stimulus, for example. Thedetected change may be used to detect anomalous cardiac activity,diagnose an anomalous cardiac conduction, and/or diagnose a cardiacdisease or condition.

The cardiac activation sequences may be indicative of about a fullcardiac cycle, a predetermined period of a cardiac cycle, apredetermined period of two or more cardiac cycles, two or more cardiaccycles, about one third of a cardiac cycle, about a QRS complex of acardiac cycle and/or an ST segment of a cardiac cycle, for example.

Methods may further involve storing information associated with one ormore cardiac signal vectors, such as cardiac activation sequenceinformation. One or more vectors and/or activation sequences may beselected, and information associated with the vectors and/or activationsequences may be stored and tracked. Methods may also involvetransmitting information associated with one or more cardiac signalvectors to a patient-external device, such as cardiac activationsequence information. Embodiments of the invention involve acquiringinformation associated with one or more of a patient's posture,activity, movement, heart-rate, heart rhythm, respiration,blood-pressure, blood gas concentration, blood chemistry, temperature,heart-sound, cardiac output, cardiac stroke volume, cardiac wall motion,peripheral or pulmonary fluid status, autonomic system status, andheart-rate variability. The acquired information may be used tofacilitate interpretation of one or more cardiac signal vectors.

Additional embodiments of methods of the present invention involvesensing two or more composite signals using three or more cardiacelectrodes, and performing a source separation that produces two or morevectors. One or more vectors are selected after performing the sourceseparation, and information associated with the vectors may be storedand used to track the selected vectors. Tracking the selected vectorsmay be useful to determine a cardiac activation sequence. Informationassociated with one or both of the selected vectors and the cardiacactivation sequence may be transmitted to a patient-external device, anddisplayed. Subsequent source separations may be performed to detectchanges in selected vectors.

Devices in accordance with the present invention include three or moreelectrodes, the electrodes configured for sensing a composite signal,thereby providing two or more composite signals. A housing configuredfor implantation in a patient includes a controller. A signal processorand a memory are coupled to the controller and configured to perform asource separation, such as a blind source separation algorithm, usingthe sensed two or more composite signals. The source separation producesone or more cardiac signal vectors associated with all or a portion ofone or more cardiac activation sequences, information from which may bestored in the memory.

The signal processor and memory may be provided in the housing, or maybe provided in a patient-external device or system such as a networkserver system and/or an advanced patient management system. The signalprocessor and the controller may be coupled to respective communicationdevices to facilitate wireless communication between the signalprocessor and controller. The controller may detect a cardiac conditionusing the vector information.

The system may include a header configured for coupling a lead to thehousing, and one or more of the electrodes may be provided on theheader. Embodiments of systems may include at least four electrodes,wherein one of the at least four electrodes does not lie spatially inthe same plane as the other electrodes.

The system may further include a lead configured for subcutaneousnon-intrathoracic placement in a patient, which may support one or moreelectrodes and/or other sensors. The sensors may be configured tomeasure one or more of a patient's posture, activity, movement, heartrate, heart rhythm, respiration, blood pressure, blood gasconcentration, blood chemistry, temperature, heart-sound, cardiacoutput, stroke volume, cardiac wall motion, peripheral or pulmonaryfluid status, autonomic system status, and heart-rate variability.Information from the sensors may be used to interpret the cardiac signalvectors.

The above summary of the present invention is not intended to describeeach embodiment or every implementation of the present invention.Advantages and attainments, together with a more complete understandingof the invention, will become apparent and appreciated by referring tothe following detailed description and claims taken in conjunction withthe accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are pictorial diagrams of an electrocardiogram (ECG)waveform for three consecutive heartbeats (FIG. 1A) and a magnifiedportion of the electrocardiogram (ECG) waveform for the first twoconsecutive heartbeats (FIG. 1B);

FIG. 2 is a polar plot of a cardiac vector superimposed over a frontalview of a thorax, with the origin of the polar plot located at the AVnode of a patient's heart;

FIG. 3A is a polar plot of cardiac vectors obtained using a sourceseparation in accordance with the present invention;

FIG. 3B illustrates polar plots of cardiac vectors obtained fromselected portions of an electrocardiogram using source separation inaccordance with the present invention;

FIG. 4 is a graph of temporal profiles of a cardiac vector useful fordiagnosing a cardiac disease in accordance with the present invention;

FIGS. 5A through 5D illustrate cardiac vectors superimposed over asectional view of the ventricles of a patient's heart;

FIG. 6A is a block diagram of a method of detecting a change in one ormore cardiac signal vectors associated with all or a portion of one ormore cardiac activation sequences based on a source separation inaccordance with the present invention;

FIG. 6B is a block diagram of another embodiment of a method ofdetecting a change in one or more cardiac signal vectors associated withall or a portion of one or more cardiac activation sequences based on asource separation in accordance with the present invention;

FIG. 7 is a top view of an implantable cardiac device in accordance withthe present invention, having at least three electrodes;

FIG. 8 is a block diagram of a cardiac activation sequence monitoringand/or tracking process in accordance with the present invention;

FIG. 9 is an illustration of an implantable cardiac device including alead assembly shown implanted in a sectional view of a heart, inaccordance with embodiments of the invention;

FIG. 10 is a top view of an implantable cardiac device in accordancewith the present invention, including an antenna electrode and alead/header arrangement;

FIG. 11 is a diagram illustrating components of a cardiac monitoringand/or stimulation device including an electrode array in accordancewith an embodiment of the present invention;

FIG. 12 is a block diagram illustrating various components of a cardiacmonitoring and/or stimulation device in accordance with an embodiment ofthe present invention;

FIG. 13 is a block diagram of a medical system that may be used toimplement system updating, coordinated patient monitoring, diagnosis,and/or therapy in accordance with embodiments of the present invention;

FIG. 14 is a block diagram illustrating uses of cardiac activationsequence monitoring and/or tracking in accordance with the presentinvention;

FIG. 15 is a block diagram of a signal separation process in accordancewith the present invention; and

FIG. 16 is an expanded block diagram of the process illustrated in FIG.15, illustrating an iterative independent component analysis inaccordance with the present invention.

While the invention is amenable to various modifications and alternativeforms, specifics thereof have been shown by way of example in thedrawings and will be described in detail below. It is to be understood,however, that the intention is not to limit the invention to theparticular embodiments described. On the contrary, the invention isintended to cover all modifications, equivalents, and alternativesfalling within the scope of the invention as defined by the appendedclaims.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

In the following description of the illustrated embodiments, referencesare made to the accompanying drawings, which form a part hereof, and inwhich is shown by way of illustration, various embodiments in which theinvention may be practiced. It is to be understood that otherembodiments may be utilized, and structural and functional changes maybe made without departing from the scope of the present invention.

An implanted device according to the present invention may include oneor more of the features, structures, methods, or combinations thereofdescribed hereinbelow. For example, a cardiac monitor or a cardiacstimulator may be implemented to include one or more of the advantageousfeatures and/or processes described below. It is intended that such amonitor, stimulator, or other implanted or partially implanted deviceneed not include all of the features described herein, but may beimplemented to include selected features that provide for uniquestructures and/or functionality. Such a device may be implemented toprovide a variety of therapeutic or diagnostic functions.

A wide variety of implantable cardiac monitoring and/or stimulationdevices may be configured to implement a cardiac activation sequencemonitoring and/or tracking methodology of the present invention. Anon-limiting, representative list of such devices includes cardiacmonitors, pacemakers, cardiovertors, defibrillators, resynchronizers,and other cardiac monitoring and therapy delivery devices. These devicesmay be configured with a variety of electrode arrangements, includingtransvenous, endocardial, and epicardial electrodes (i.e., intrathoracicelectrodes), and/or subcutaneous, non-intrathoracic electrodes,including can, header, and indifferent electrodes, and subcutaneousarray or lead electrodes (i.e., non-intrathoracic electrodes).

Embodiments of the present invention may be implemented in the contextof a wide variety of cardiac devices, such as those listed above, andare referred to herein generally as patient-internal medical devices(PIMD) for convenience. A PIMD implemented in accordance with thepresent invention may incorporate one or more of the electrode typesidentified above and/or combinations thereof.

Cardiac activation sequence monitoring and/or tracking systems of thepresent invention employ more than two electrodes of varying location,and possibly of varying configuration. In one embodiment, for example,two or more electrodes may conveniently be located on the PIMD header,whereas the can of the PIMD itself may be the third electrode. Inanother embodiment, one electrode may be located on the PIMD header,another is the can electrode, and a third may be a PIMD antenna used forRF telemetry.

Electrocardiogram (ECG) signals originate from electrophysiologicalsignals propagated through the heart muscle, which provide for thecardiac muscle contraction that pumps blood through the body. A sensedECG signal is effectively a superposition of all the depolarizationsoccurring within the heart that are associated with cardiac contraction,along with noise components. The propagation of the depolarizationsthrough the heart may be referred to as a depolarization wavefront. Thesequence of depolarization wavefront propagation through the chambers ofthe heart, providing the sequential timing of the heart's pumping, isdesignated an activation sequence.

A signal separation algorithm may be implemented to separate activationsequence components of ECG signals, and produce one or more cardiacsignal vectors associated with all or a portion of one or more cardiacactivation sequences based on the separation. The activation sequencecomponents may be considered as the signal sources that make up the ECGsignals, and the signal separation process may be referred to as asource separation process or simply source separation. One illustrativesignal source separation methodology useful for producing cardiac signalvectors associated with cardiac activation sequences is designated blindsource separation, which will be described in further detail below. Ingeneral, the quality of the electrocardiogram or electrogram sensed fromone pair of electrodes of a PIMD depends on the orientation of theelectrodes with respect to the depolarization wavefront produced by theheart. The signal sensed on an electrode bi-pole is the projection ofthe ECG vector in the direction of the bi-pole. Cardiac activationsequence monitoring and/or tracking algorithms of the present inventionadvantageously exploit the strong correlation of signals from a commonorigin (the heart) across spatially distributed electrodes.

Referring to FIGS. 1A and 1B, an ECG waveform 100 describes theactivation sequence of a patient's heart as recorded, for example, by abi-polar cardiac sensing electrode. The graph of FIG. 1A illustrates anexample of the ECG waveform 100 for three heartbeats, denoted as a firstheartbeat 110, a second heartbeat 120, and a third heartbeat 130. FIG.1B is a magnified view of the first two heartbeats 110, 120 of the ECGwaveform identified by bracket 1B in FIG. 1A.

Referring to the first heartbeat 110, the portion of the ECG waveformrepresenting depolarization of the atrial muscle fibers is referred toas a P-wave 112. Depolarization of the ventricular muscle fibers iscollectively represented by a Q 114, R 116, and S 118 waves of the ECGwaveform 100, typically referred to as the QRS complex, which is awell-known morphologic feature of electrocardiograms. Finally, theportion of the waveform representing repolarization of the ventricularmuscle fibers is known as a T wave 119. Between contractions, the ECGwaveform returns to an isopotential level.

The sensed ECG waveform 100 illustrated in FIGS. 1A and 1B is typical ofa far-field ECG signal, effectively a superposition of all thedepolarizations occurring within the heart that result in contraction.The ECG waveform 100 may also be obtained indirectly, such as by using asignal separation methodology. Signal separation methodologies, such asblind source separation (BSS), are able to separate signals fromindividual sources that are mixed together into a composite signal. Themain principle of signal separation works on the premise that spatiallydistributed electrodes collect components of a signal from a commonorigin (e.g., the heart) with the result that these components may bestrongly correlated to each other. In addition, these components mayalso be weakly correlated to components of another origin (e.g., noise).A signal separation algorithm may be implemented to separate thesecomponents according to their sources and produce one or more cardiacsignal vectors associated with all or a portion of one or more cardiacactivation sequences based on the source separation.

FIG. 2 illustrates a convenient reference for describing cardiac signalvectors associated with a depolarization wavefront. FIG. 2 is a polarplot 200 of a cardiac vector 240 superimposed over a frontal view of athorax 220, with the origin of the polar plot located at a patient'sheart 250, specifically, the atrioventricular (AV) node of the heart250. The heart 250 is a four-chambered pump that is largely composed ofa special type of striated muscle, called myocardium. Two major pumpsoperate in the heart, and they are a right ventricle 260, which pumpsblood into pulmonary circulation, and a left ventricle 270, which pumpsblood into the systemic circulation. Each of these pumps is connected toits associated atrium, called a right atrium 265 and a left atrium 275.

The cardiac vector 240 is describable as having an angle, in degrees,about a circle of the polar plot 200, and having a magnitude,illustrated as a distance from the origin of the tip of the cardiacvector 240. The polar plot 200 is divided into halves by a horizontalline indicating 0 degrees on the patient's left, and +/−180 degrees onthe patient's right, and further divided into quadrants by a verticalline indicated by −90 degrees at the patient's head and +90 degrees onthe bottom. The cardiac vector 240 is projectable onto thetwo-dimensional plane designated by the polar plot 200.

The cardiac vector 240 is a measure of all or a portion of theprojection of a heart's activation sequence onto the polar plot 200. Theheart possesses a specialized conduction system that ensures, undernormal conditions, that the overall timing of ventricular and atrialpumping is optimal for producing cardiac output, the amount of bloodpumped by the heart per minute. As described earlier, the normalpacemaker of the heart is a self-firing unit located in the right atriumcalled the sinoatrial node. The electrical depolarization generated bythis structure activates contraction of the two atria. Thedepolarization wavefront then reaches the specialized conduction systemusing conducting pathways within and between the atria. Thedepolarization is conducted to the atrioventricular node, andtransmitted down a rapid conduction system composed of the right andleft bundle branches, to stimulate contraction of the two ventricles.

The normal pacemaker and rapid conduction system are influenced byintrinsic automatic activity and by the autonomic nervous system, whichmodulates heart rate and the speed with which electrical depolarizationsare conducted through the specialized conduction system. There are manydiseases that interfere with the specialized conduction system of theheart, and many result in abnormally fast, slow, or irregular heartrhythms.

The cardiac vector 240 may be, for example, associated with the entirecardiac cycle, and describe the mean magnitude and mean angle of thecardiac cycle. Referring now to FIG. 3A, a polar plot 300 is illustratedof separate portions of the cardiac cycle that may make up the cardiacvector 240 of FIG. 2. As is illustrated in FIG. 3A, a QRS vector 310 anda P vector 320 are illustrated having approximately 60 degree and 30degree angles, respectively. The QRS vector 310 may also be referred toas the QRS axis, and changes in the direction of the QRS vector may bereferred to as QRS axis deviations.

The QRS vector 310 represents the projection of the mean magnitude andangle of the depolarization wavefront during the QRS portion of thecardiac cycle onto the polar plot 300. The P vector 320 represents theprojection of the mean magnitude and angle of the depolarizationwavefront during the P portion of the cardiac cycle onto the polar plot300. The projection of any portion of the depolarization wavefront maybe represented as a vector on the polar plot 300.

Further, any number of cardiac cycles may be combined to provide astatistical sample that may be represented by a vector as a projectiononto the polar plot 300. Likewise, portions of the cardiac cycle overmultiple cardiac cycles may also be combined, such as combining aweighted summation of only the P portion of the cardiac cycle overmultiple cardiac cycles, for example.

Referring now to FIGS. 1 through 3A, the first, second, and thirdcardiac cycles 110, 120, and 130 may be analyzed using a window 140(FIG. 1) applied concurrently to signals sensed by three or more cardiacsense electrodes. The ECG waveform signals 100 from all the senseelectrodes, during the window 140, may be provided to a signalprocessor. The signal processor may then perform a source separationthat provides the cardiac vector 240 (FIG. 2). The cardiac vector 240then represents the orientation and magnitude of the cardiac vector thatis effectively an average over all three cardiac cycles 110, 120, and130.

Other windows are also useful. For example, a window 150 and a window160 may provide each full cardiac cycle, such as the cardiac cycle 120and the cardiac cycle 130 illustrated in FIG. 1, to a controller foranalysis. The windows 150, 160 may be useful for beat-to-beat analysis,where the angle, magnitude, or other useful parameter from the separatedcardiac vector 240 is compared between consecutive beats, or trended,for example.

Examples of other useful windows include a P-window 152, a QRS window154, and an ST window 155 (FIG. 1) that provide within-beat vectoranalysis capability, such as by providing the P-vector 320 and theQRS-vector 310 illustrated in FIG. 3A. Providing a P-window 162 and/or aQRS-window 164, and/or an ST window 165 to subsequent beats, such as tothe consecutive cardiac cycle 130 illustrated in FIG. 1, provides forsubsequent separations that may provide information for tracking andmonitoring changes and/or trends of windowed portions of the cardiaccycle or statistical samples of P, QRS, or T waves over more than 1beat.

Referring now to FIG. 3B, polar plots of cardiac vectors obtained fromselected portions of an electrocardiogram are illustrated. In general,it may be desirable to define one or more detection windows associatedwith particular segments of a given patient's cardiac cycle. Thedetection windows may be associated with cardiac signal features, suchas P, QRS, ST, and T wave features, for example. The detection windowsmay also be associated with other portions of the cardiac cycle thatchange in character as a result of changes in the pathology of apatient's heart. Such detection windows may be defined as fixed ortriggerable windows.

Detection windows may include unit step functions to initiate andterminate the window, or may be tapered or otherwise initiate andterminate using smoothing functions such as Bartlett, Bessel,Butterworth, Hanning, Hamming, Chebyshev, Welch, or other functionsand/or filters. The detection windows associated with particular cardiacsignal features or segments may have widths sufficient to sense cardiacvectors resulting from normal or expected cardiac activity. Aberrant orunexpected cardiac activity may result in the failure of a given cardiacvector to fall within a range indicative of normal cardiac behavior.Detection of a given cardiac vector beyond a normal range may triggerone or more operations, including increased monitoring or diagnosticoperations, therapy delivery, patient or physician alerting,communication of warning and/or device/physiological data to an externalsystem (e.g., advanced patient management system) or other responsiveoperation.

An ECG signal 305 is plotted in FIG. 3B as a signal amplitude 350 on theordinate versus time on the abscissa. One cardiac cycle is illustrated.The P portion of the ECG signal 305 may be defined using a P-window 335that opens at a time 336 and closes at a time 337. A source separationperformed on the ECG signal 305 within the P-window 335 produces the Pvector 310 illustrated on a polar plot 330. The angle of the P vector310 indicates the angle of the vector summation of the depolarizationwavefront during the time of the P-window 335 for the ECG signal 305.

The ST portion of the ECG signal 305 may be defined using an ST-window345 that opens at a time 346 and closes at a time 347. A sourceseparation performed on the ECG signal 305 within the ST-window 345produces the ST vector 350 illustrated on a polar plot 340. The angle ofthe ST vector 350 indicates the angle of the vector summation of thedepolarization wavefront during the time of the ST-window 345 for theECG signal 305.

The P vector 310 and the ST vector 350 may be acquired as baselines, forfuture comparisons. If baselines for the P vector 310 and the ST vector350 are already established, the P vector 310 and ST vector 350 may becompared relative to their baselines for monitoring and trackingpurposes. As indicated above, detection of P vector 310 or ST vector 350beyond a predetermined range may trigger one or more responsiveoperations.

Cardiac activation sequence monitoring and tracking, to monitor changesand/or trends as described above, may be useful to determine initialactivation sequences, and track acute and chronic changes in theactivation sequences. Information from the patient's activation sequenceis valuable for identification, discrimination, and trending ofconditions such as conduction anomalies (e.g. AV block, bundle branchblock, retrograde conduction) and cardiac arrhythmias (e.g.discriminating between supraventricular tachycardia versus ventriculartachycardia, reentrant supraventricular tachycardia versus atrialfibrillation, or other desirable discrimination.) In addition tobaseline establishment, monitoring, and tracking, activation sequenceinformation may also be useful for determining pace capture forautocapture/autothreshold algorithms, adjustment, optimization, orinitiation of cardiac resynchronization therapy, and optimization orinitiation of anti-arrhythmia therapies, for example.

FIG. 4 illustrates another convenient reference for describing cardiacsignal vectors associated with a depolarization wavefront. FIG. 4 is agraph 400 of temporal profiles of a measure of a cardiac vector usefulfor diagnosing diseases and anomalous conditions in accordance with thepresent invention. The graph 400 contains a first temporal profile 430of a cardiac vector, and a second temporal profile 440 of the samecardiac vector after a change has occurred. An abscissa 420 of the graph400 is time related, and an ordinate 410 of the graph 400 is related toa measure of the cardiac vector.

The ordinate 410 may be, for example, the angle of the cardiac vector. Anon-limiting, non-exhaustive list of measures of a vector useful for theordinate 410 includes: angle; magnitude; variance; power spectraldensity; rate of change of angle; rate of change of magnitude; rate ofchange of variance; or other measure indicative of a change in thecardiac activation sequence. As an example, consider the angle of the Pvector 320 illustrated in FIG. 3A. In this example, the ordinate 410would be indicated in degrees, with the first temporal profile 430varying from around 30 degrees. The abscissa 420 may be time, designatedin cardiac cycles, with a measure made of the P vector 320 for everycardiac cycle. The angle of the P vector 320 may be plotted on the graph400 at any interval of cardiac cycles, thereby displaying variance andtrends in the angle of the P vector 320 over many cardiac cycles.

After some change occurs, such as a pathological change in the patient'sheart, the second temporal profile 440 may be plotted using cardiaccycles occurring after the change. As is evident in the second temporalprofile 440 versus the first temporal profile 430, the variance of thesecond temporal profile 440 is significantly larger than the variance ofthe first temporal profile 430. Changes such as this may be detected andused to diagnose, verify and/or monitor diseases and/or cardiacconditions in accordance with the present invention.

FIGS. 5A through 5D illustrate cardiac vectors superimposed over asectional view of the ventricles of a patient's heart 500. Referring toFIG. 5A, the ventricular portion of a patient's heart is illustratedhaving a right ventricle 510 and a left ventricle 520 separated by theheart's septum. The specialized conduction system includes anatrioventricular node 550, which is used as the origin for cardiacvectors, such as a mean QRS vector 525.

A right bundle branch 530 conducts the depolarization wavefront from theatrioventricular node 550 to the wall of the right ventricle 510.Illustrated in the wall of the right ventricle 510 are a series ofvectors 511-517, indicating the magnitude and angle of a local portionof the depolarization wavefront as it travels along the right ventricle510.

A left bundle branch 540 conducts the depolarization wavefront from theatrioventricular node 550 to the wall of the left ventricle 520.Illustrated in the wall of the left ventricle 510 are a series ofvectors 501-507, indicating the magnitude and angle of a local portionof the depolarization wavefront as it travels along the left ventricle520.

The mean QRS vector 525 is the vector summation of the vectors 511-517and the vectors 501-507. The mean QRS vector 525 may be typical of ahealthy heart, here illustrated at about 40 degrees angle if using thepolar plot of FIG. 3A. The mean QRS vector 525 varies from patient topatient depending on, for example, patient posture, and normalanatomical variation.

Referring now to FIG. 5B, the wall of the left ventricle 520 isenlarged, or hypertrophied, relative to FIG. 5A. In FIG. 5B, a dottedline 560 represents the wall of the left ventricle 520 in FIG. 5A,before hypertrophy. A series of local vectors 561-567 illustrate thelarger local contribution to the mean QRS vector 525 from thehypertrophy related vectors 561-567 relative to the normal series ofleft ventricle vectors 501-507.

FIG. 5C illustrates how the mean QRS vector 525 from a normal heart maychange to a mean hypertrophied QRS vector 565 after hypertrophy hasoccurred. For example, a PIMD may be implanted in a patient, and aninitial analysis provides a baseline mean QRS vector 525 for thepatient, indicative of a normal condition of the left ventricle 520.After a period of time, the patient's heart may be subject tohypertrophy. An analysis performed post-hypertrophy may result infinding the mean hypertrophied QRS vector 565. This change may be usedto diagnose, verify and/or monitor hypertrophy of the patient's leftventricle.

Another example of a pathological change that may be diagnosed and/orverified using embodiments of the present invention is a lessening orloss of blood supply to a portion of the heart, such as through atransient ischemia or myocardial infarction. The sectional view in FIG.5D illustrates the left ventricle 520 having an infarcted portion 570 ofthe ventricular wall. As is evident in the infarcted portion 570, nodepolarization is occurring, so only local depolarization vectors571-574 contribute to the mean cardiac vector from the left ventricle520. The infarction results in a change, for example, of the detectedmean QRS vector 525 to an infarcted mean QRS vector 580. Other vectorssuch as the ST vector may also show the change. This change is evidentas the angle of the cardiac vector moves from the second quadrant beforeinfarction, to the third quadrant after infarction.

A PIMD that detects a change such as is illustrated in FIG. 5D has thepotential to alert the patient and/or physician to a loss or lesseningof blood supply to a portion of the heart muscle before permanent damageoccurs. Early detection may result in greatly reduced morbidity fromthese kinds of events.

FIG. 6A is a block diagram of a method 600 of detecting a change in oneor more cardiac signal vectors associated with all or a portion of oneor more cardiac activation sequences based on a source separation inaccordance with the present invention. A baseline is established 610,providing information that may be monitored or tracked relative to apatient's electrophysiological signals. The baseline 610 may beestablished from an initial source separation, that provides initialcardiac signal information as a baseline. Alternately, or additionally,the baseline 610 may be established by a PIMD manufacturer from clinicaldata, or a patient's baseline 610 may be established by a clinicianbefore, during, or after a PIMD implant procedure. The baseline 610 maybe established as a rolling average of recent patient information fromprior source separations, for example.

Evaluation criteria is established 620 to provide an index forcomparison to the baseline 610. For example, the evaluation criteria 620may be any parameter or characteristic determinable or measurable fromthe patient's electrophysiology information. A non-exhaustive,non-limiting list of evaluation criteria 620 includes: an angle changeof one or more cardiac signal vectors; a magnitude change of one or morecardiac signal vectors; a variance change of one or more cardiac signalvectors; a power spectral density change of the angle of one or morecardiac signal vectors; a power spectral density change of the magnitudeof one or more cardiac signal vectors; a trajectory change of one ormore cardiac signal vectors; a temporal profile change of one or morecardiac signal vectors; a rate of change of angle of one or more cardiacsignal vectors; a rate of change of magnitude of one or more cardiacsignal vectors; a rate of change of variance of one or more cardiacsignal vectors; a rate of change of temporal profile of one or morecardiac signal vectors; a trend of the angle of one or more cardiacsignal vectors; a trend of the magnitude of one or more cardiac signalvectors; a trend of the variance of one or more cardiac signal vectors;and a trend of the temporal profile of one or more cardiac signalvectors.

For example, an initial source separation may be performed by a PIMD ona patient post-implant. The separation may produce the baseline 610 ofthe patient's average full cardiac cycle, such as the cardiac vector 240illustrated in FIG. 2. The vector 240 may have a characteristic, such asthe angle, determined as +45 degrees. The evaluation criteria 620 maybe, for example, that the patient's average full cardiac cycle vector'sangle should be within +40 to +50 degrees.

A comparison 630 is performed to determine the latest patientinformation relative to the baseline 610. For example, the results of alatest source separation algorithm may provide the latest average fullcardiac cycle vector's angle for the patient. Continuing with the aboveexample, the comparison 630 may check the latest angle of the patient'saverage full cardiac cycle vector's angle against the +40 to +50 degreecriteria.

A decision 640 selects an outcome based on the comparison 630. If thecriteria is met, for example if the latest angle is within +40 to +50degrees as outlined above, then a pattern A 650 is considered to be thepatient's latest condition. For example, the pattern A 650 may bedefined as an insufficient change to require some sort of action by thePIMD. If the criteria 620 is not met at decision 640, then a pattern Acomplement 660 condition is considered to be the patient's latestcondition.

The pattern A complement 660 condition may be defined as requiring somesort of action by the PIMD, such as reporting the condition, furtherevaluating the patient's cardiac rhythms, preparing a defibrillator fora shock, or other desired action.

FIG. 6B is a block diagram of another embodiment of a method 605 ofdetecting a change in one or more cardiac signal vectors associated withall or a portion of one or more cardiac activation sequences, when thecriteria for baseline shift includes two criteria. It is contemplatedthat any number of criteria may be used or combined in accordance withthe present invention. The use of two criteria with reference to FIG. 6Bis for purposes of explanation as to how to extend methods of thepresent invention to multiple criteria, and is not intended as alimiting example.

A baseline is established 612, providing information that may bemonitored or tracked from a patient's electrophysiological signals. Thebaseline 612 may be established from an initial source separation, thatprovides initial cardiac signal information as a baseline. Alternately,or additionally, the baseline 612 may be established by a PIMDmanufacturer from clinical data, or a patient's baseline 612 may beestablished by a clinician before, during, or after a PIMD implantprocedure. The baseline 612 may be established as a rolling average ofrecent patient information from prior source separations, for example.

Evaluation criteria are established 622 to provide indices forcomparison to the baseline 612. For example, the evaluation criteria 622may be any parameters or characteristics determinable or measurable fromthe patient's electrophysiology information. A non-exhaustive,non-limiting list of evaluation criteria 622 includes those describedpreviously with respect to FIG. 6A. It is further contemplated that asingle criterion may be compared with respect to multiple baselines,and/or that multiple criteria may each be compared with respect to theirown unique baseline established for each particular criterion.

Baselines may be pre-defined using, for example, clinical data, and/orbaselines may be established using initial source separations. Forexample, and described in more detail below, a source separation mayprovide an orthogonal coordinate system, with vectors described using aseries of coefficients matched to a series of unit direction vectors.One or more angles may be calculated using trigonometric identities toindicate a vector's direction relative to other vectors in thecoordinate system. Subsequent source separations provide revised sets ofcoefficients, from which changes in vector direction may be determinedusing the same trigonometric identities. In an n-dimensional space,(n−1) angles may be resolved and used for comparison and tracking inaccordance with the present invention.

For example, an initial source separation may be performed by a PIMD ona patient post-implant. The separation may produce the baseline 612 ofthe patient's cardiac cycle, such as the QRS-vector 310 and the P-vector320 illustrated in FIG. 3A. The QRS-vector 310 may have the angledetermined as +45 degrees. The P-vector 320 may have the angledetermined as +28 degrees. The evaluation criteria 622 may be, forexample, that the patient's QRS-vector's angle should be within +40 to+50 degrees and that the patient's P-vector angle should be within +25to +30 degrees.

A comparison 632 is performed to determine the latest patientinformation relative to the baseline 612. For example, the results of alatest source separation algorithm may provide the latest angles of theQRS-vector and P-vector for the patient. Continuing with the aboveexample, the comparison 632 may check the latest angles of the patient'sQRS-vector and P-vector against the +40 to +50 degree and +25 to +30degree criteria respectively.

A first decision 642 selects a first outcome based on the comparison632. If the first criteria is met, for example if the latest angle ofthe QRS-vector is within +40 to +50 degrees as outlined above, then apattern A 652 is considered to be the patient's latest condition. Forexample, the pattern A 652 may be defined as an insufficient change torequire some sort of action by the PIMD. If the criteria 622 is not metat decision 642, then a pattern A complement 662 condition is consideredto be the patient's latest condition. The pattern A complement 662condition may be defined as requiring some sort of action by the PIMD,such as reporting the condition, further evaluating the patient'scardiac rhythms, preparing a defibrillator for a shock, or other desiredaction.

A second criteria decision 672 is performed to check for a secondoutcome based on the second criteria. If the second criteria is met, forexample if the latest angle of the P-vector is within +25 to +30 degreesas outlined above, then a pattern B 682 is considered to be thepatient's latest condition. For example, the pattern B 682 may bedefined as an insufficient change to require some sort of second actionby the PIMD. If the criteria 622 is not met at decision 672, then apattern B complement 692 condition is considered to be the patient'slatest condition. The pattern B complement 692 condition may be definedas requiring some sort of second action by the PIMD.

Table 1 below provides a non-limiting non-exhaustive list of conditionsthat may be detected by monitoring and/or tracking cardiac activationsequences in accordance with the present invention.

TABLE 1 Conditions associated with QRS Axis Deviations First Source(Normal −30 to +90 degrees) Left Axis Deviation (LAD): ≧−30° LeftAnterior Fascicular Block (LAFB) axis −45° to −90° Some cases ofinferior myocardial infarction with QR complex Inferior MyocardialInfarction + LAFB in same patient (QS or QRS complex) Some cases of leftventricular hypertrophy Some cases of left bundle branch block Ostiumprimum Atrial Septal Defect and other endocardial cushion defects Somecases of Wolff-Parkinson-White syndrome syndrome (large negative deltawave) Right Axis Deviation (RAD): ≧+90° Left Posterior Fascicular Block(LPFB): Many causes of right heart overload and pulmonary hypertensionHigh lateral wall Myocardial Infarction with QR or QS complex Some casesof right bundle branch block Some cases of Wolff-Parkinson-Whitesyndrome syndrome Children, teenagers, and some young adults Bizarre QRSaxis: +150° to −90° Dextrocardia Some cases of complex congenital heartdisease (e.g., transposition) Some cases of ventricular tachycardiaSecond Source QRS Axis Deviation Left anterior fascicular block (LAFB)Right ventricular hypertrophy Left bundle branch block Acute MyocardialInfarction: Hypertensive heart disease Coronary artery diseaseIdiopathic conducting system disease Acute MyocardialInfarction—inferior left ventricular free wall accessory pathway(Wolff-Parkinson-White syndrome) Posteroseptal accessory pathway leftposterior fascicular block Chronic Obstructive Pulmonary Disease(uncommon - 10%) Other conduction defects: left ventricular hypertrophyRight bundle branch block Elevated diaphragm: R anterior hemiblockPregnancy Pacing of R ventricle Abdominal mass Pulmonary conditionsAscites Pulmonary hypertension Tumor Chronic Obstructive PulmonaryDisease Conduction defects: Emphysema/bronchitis R ventricular (apical)pacing Pulmonary emboli/infarcts Systemic hypertension, esp. chronicCongenital defects Valvular lesions Rheumatic heart disease Pulmonicstenosis Aortic regurgitation Mitral regurgitation Mitral stenosisCoarctation of the aorta Tricuspid regurgitation Hyperkalemia Pulmonicstenosis Normal variant in obese and in elderly Pulmonic regurgitation

FIG. 7 is a top view of a PIMD 782 in accordance with the presentinvention, having at least three electrodes. Although multipleelectrodes are illustrated in FIG. 7 as located on the can, typicallythe can includes one electrode, and other electrodes are coupled to thecan using a lead. The PIMD 782 shown in the embodiment illustrated inFIG. 7 includes a first electrode 781 a, a second electrode 781 b, and athird electrode 781 c provided with a can 703. The PIMD 782 detects andrecords cardiac activity. The can 703 is illustrated as incorporating aheader 789 that may be configured to facilitate removable attachmentbetween one or more leads and the can 703. The can 703 may include anynumber of electrodes positioned anywhere in or on the can 703, such asoptional electrodes 781 d, 781 e, 781 f, and 781 g. Each electrode pairprovides one vector available for the sensing of ECG signals.

FIG. 8 is a block diagram of a process 850 useful for extracting vectorinformation for cardiac activation sequence monitoring and tracking inaccordance with the present invention. The process 850 starts at block851, where multiple concurrent measurements are obtained betweenmultiple respective electrode pairs, chosen from at least threeelectrodes. Block 852 provides for pre-filtering the collected signalswith, for example, a linear-phase filter to suppress broadly incoherentnoise, and to generally maximize the signal-to-noise ratio.

Block 853 indicates the computation of the cross-correlation matrix,which may be averaged over a relatively short time interval, such asabout 1 second. This block enhances the components that are mutuallycorrelated. Block 854 is then provided for computation of theeigenvalues of the cross-correlation matrix. The smaller eigenvalues,normally associated with noise, may then be used at block 855 toeliminate noise, by removing the noise components of the compositesignals associated with those eigenvalues.

At block 856, signals may be separated from the composite signals usingthe eigenvalues. Separated sources may be obtained by taking linearcombinations of the recorded signals, as specified in the eigenvectorscorresponding to the larger eigenvalues. Optionally, block 857 providesfor performing additional separation based on higher order statistics,if the cardiac signal or other signal of interest is not found among thesignals separated at block 856.

At block 858, the cardiac signal may be identified based on theselection criteria, along with its associated vector, among theseparated signals. Typically, the cardiac signal is found among thesignals associated with the largest eigenvalues. Vector selection andupdating systems and methods are further described in commonly assignedco-pending U.S. Pat. No. 7,706,866, which is hereby incorporated hereinby reference.

For purposes of illustration, and not of limitation, various embodimentsof devices that may use cardiac activation sequence monitoring andtracking in accordance with the present invention are described hereinin the context of PIMD's that may be implanted under the skin in thechest region of a patient. A PIMD may, for example, be implantedsubcutaneously such that all or selected elements of the device arepositioned on the patient's front, back, side, or other body locationssuitable for monitoring cardiac activity and/or delivering cardiacstimulation therapy. It is understood that elements of the PIMD may belocated at several different body locations, such as in the chest,abdominal, or subclavian region with electrode elements respectivelypositioned at different regions near, around, in, or on the heart.

The primary housing (e.g., the active or non-active can) of the PIMD,for example, may be configured for positioning outside of the rib cageat an intercostal or subcostal location, within the abdomen, or in theupper chest region (e.g., subclavian location, such as above the thirdrib). In one implementation, one or more leads incorporating electrodesmay be located in direct contact with the heart, great vessel orcoronary vasculature, such as via one or more leads implanted by use ofconventional transvenous delivery approaches. In another implementation,one or more electrodes may be located on the primary housing and/or atother locations about, but not in direct contact with the heart, greatvessel or coronary vasculature.

In a further implementation, for example, one or more electrodesubsystems or electrode arrays may be used to sense cardiac activityand/or deliver cardiac stimulation energy in a PIMD configurationemploying an active can or a configuration employing a non-active can.Electrodes may be situated at anterior and/or posterior locationsrelative to the heart. Examples of useful electrode locations andfeatures that may be incorporated in various embodiments of the presentinvention are described in commonly owned, co-pending U.S. PublicationNo. 2004/0230230 and U.S. Pat. Nos. 7,299,086 and 7,499,750, which arehereby incorporated herein by reference.

Certain configurations illustrated herein are generally described ascapable of implementing various functions traditionally performed by animplantable cardioverter/defibrillator (ICD), and may operate innumerous cardioversion/defibrillation modes as are known in the art.Examples of ICD circuitry, structures and functionality, aspects ofwhich may be incorporated in a PIMD of a type that may benefit fromcardiac activation sequence monitoring and/or tracking are disclosed incommonly owned U.S. Pat. Nos. 5,133,353; 5,179,945; 5,314,459;5,318,597; 5,620,466; and 5,662,688, which are hereby incorporatedherein by reference.

In particular configurations, systems and methods may perform functionstraditionally performed by pacemakers, such as providing various pacingtherapies as are known in the art, in addition tocardioversion/defibrillation therapies. Examples of pacemaker circuitry,structures and functionality, aspects of which may be incorporated in aPIMD of a type that may benefit from cardiac activation sequencemonitoring and/or tracking methods and implementations are disclosed incommonly owned U.S. Pat. Nos. 4,562,841; 5,284,136; 5,376,106;5,036,849; 5,540,727; 5,836,987; 6,044,298; and 6,055,454, which arehereby incorporated herein by reference. It is understood that PIMDconfigurations may provide for non-physiologic pacing support inaddition to, or to the exclusion of, bradycardia and/or anti-tachycardiapacing therapies.

A PIMD useful for extracting vector information for cardiac activationsequence monitoring and tracking in accordance with the presentinvention may implement diagnostic and/or monitoring functions as wellas provide cardiac stimulation therapy. Examples of cardiac monitoringcircuitry, structures and functionality, aspects of which may beincorporated in a PIMD of a type that may benefit from cardiacactivation sequence monitoring and/or tracking methods andimplementations are disclosed in commonly owned U.S. Pat. Nos.5,313,953; 5,388,578; and 5,411,031, which are hereby incorporatedherein by reference.

Various embodiments described herein may be used in connection withcongestive heart failure (CHF) monitoring, diagnosis, and/or therapy. APIMD of the present invention may incorporate CHF features involvingdual-chamber or bi-ventricular pacing therapy, cardiac resynchronizationtherapy, cardiac function optimization, or other CHF relatedmethodologies. For example, any PIMD of the present invention mayincorporate features of one or more of the following references:commonly owned U.S. Pat. Nos. 6,411,848; 6,285,907; 4,928,688;6,459,929; 5,334,222; 6,026,320; 6,371,922; 6,597,951; 6,424,865;6,542,775; and 7,260,432, each of which is hereby incorporated herein byreference.

A PIMD may be used to implement various diagnostic functions, which mayinvolve performing rate-based, pattern and rate-based, and/ormorphological tachyarrhythmia discrimination analyses. Subcutaneous,cutaneous, and/or external sensors may be employed to acquirephysiologic and non-physiologic information for purposes of enhancingtachyarrhythmia detection and termination. It is understood thatconfigurations, features, and combination of features described in thepresent disclosure may be implemented in a wide range of implantablemedical devices, and that such embodiments and features are not limitedto the particular devices described herein.

Referring now to FIG. 9, the implantable device illustrated in FIG. 9 isan embodiment of a PIMD that may benefit from cardiac sequencemonitoring and tracking in accordance with the present invention. Inthis example, the implantable device includes a cardiac rhythmmanagement device (CRM) 900 including an implantable pulse generator 905electrically and physically coupled to an intracardiac lead system 910.

Portions of the intracardiac lead system 910 are inserted into thepatient's heart 990. The intracardiac lead system 910 includes one ormore electrodes configured to sense electrical cardiac activity of theheart, deliver electrical stimulation to the heart, sense the patient'stransthoracic impedance, and/or sense other physiological parameters,e,g, cardiac chamber pressure or temperature. Portions of the housing901 of the pulse generator 905 may optionally serve as a can electrode.

Communications circuitry is disposed within the housing 901 forfacilitating communication between the pulse generator 905 and anexternal communication device, such as a portable or bed-sidecommunication station, patient-carried/worn communication station, orexternal programmer, for example. The communications circuitry may alsofacilitate unidirectional or bidirectional communication with one ormore implanted, external, cutaneous, or subcutaneous physiologic ornon-physiologic sensors, patient-input devices and/or informationsystems.

The pulse generator 905 may optionally incorporate a motion detector 920that may be used to sense patient activity as well as variousrespiratory and cardiac related conditions. For example, the motiondetector 920 may be optionally configured to sense snoring, activitylevel, and/or chest wall movements associated with respiratory effort,for example. The motion detector 920 may be implemented as anaccelerometer positioned in or on the housing 901 of the pulse generator905. If the motion sensor is implemented as an accelerometer, the motionsensor may also provide respiratory, e.g. rales, coughing, and cardiac,e.g. S1-S4 heart sounds, murmurs, and other acoustic information.

The lead system 910 and pulse generator 905 of the CRM 900 mayincorporate one or more transthoracic impedance sensors that may be usedto acquire the patient's respiratory waveform, or otherrespiratory-related information. The transthoracic impedance sensor mayinclude, for example, one or more intracardiac electrodes 941, 942,951-955, 963 positioned in one or more chambers of the heart 990. Theintracardiac electrodes 941, 942, 951-955, 963 may be coupled toimpedance drive/sense circuitry 930 positioned within the housing of thepulse generator 905.

In one implementation, impedance drive/sense circuitry 930 generates acurrent that flows through the tissue between an impedance driveelectrode 951 and a can electrode on the housing 901 of the pulsegenerator 905. The voltage at an impedance sense electrode 952 relativeto the can electrode changes as the patient's transthoracic impedancechanges. The voltage signal developed between the impedance senseelectrode 952 and the can electrode is detected by the impedance sensecircuitry 930. Other locations and/or combinations of impedance senseand drive electrodes are also possible.

The lead system 910 may include one or more cardiac pace/senseelectrodes 951-955 positioned in, on, or about one or more heartchambers for sensing electrical signals from the patient's heart 990and/or delivering pacing pulses to the heart 990. The intracardiacsense/pace electrodes 951-955, such as those illustrated in FIG. 9, maybe used to sense and/or pace one or more chambers of the heart,including the left ventricle, the right ventricle, the left atriumand/or the right atrium. The lead system 910 may include one or moredefibrillation electrodes 941, 942 for deliveringdefibrillation/cardioversion shocks to the heart.

The pulse generator 905 may include circuitry for detecting cardiacarrhythmias and/or for controlling pacing or defibrillation therapy inthe form of electrical stimulation pulses or shocks delivered to theheart through the lead system 910. The pulse generator 905 may alsoincorporate circuitry, structures and functionality of the implantablemedical devices disclosed in commonly owned U.S. Pat. Nos. 5,203,348;5,230,337; 5,360,442; 5,366,496; 5,397,342; 5,391,200; 5,545,202;5,603,732; and 5,916,243; 6,360,127; 6,597,951; and 6,993,389, which arehereby incorporated herein by reference.

FIG. 10 is a top view of a PIMD 1082 in accordance with the presentinvention, having at least three electrodes. One electrode isillustrated as an antenna 1005 of the PIMD that may also be used forradio-frequency (RF) communications. The PIMD 1082 shown in theembodiment illustrated in FIG. 10 includes a first electrode 1098 and asecond electrode 1099 coupled to a can 1003 through a header 1089, viaan electrode module 1096. The first electrode 1098 and second electrode1099 may be located on a lead 1083 (single or multiple lead, orelectrode array), or may be located directly in or on the electrodemodule 1096.

The PIMD 1082 detects and records cardiac activity. The can 1003 isillustrated as incorporating the header 1089. The header 1089 may beconfigured to facilitate removable attachment between an electrodemodule 1096 and the can 1003, as is shown in the embodiment depicted inFIG. 10. The header 1089 includes a female coupler 1092 configured toaccept a male coupler 1093 from the electrode module 1096. The malecoupler 1093 is shown having two electrode contacts 1094, 1095 forcoupling one or more electrodes 1098, 1099 through the electrode module1096 to the can 1003. An electrode 1081 h and an electrode 1081 k areillustrated on the header 1089 of the can 1003 and may also be coupledthrough the electrode module 1096 to the can 1003. The can 1003 mayalternatively, or in addition to the header electrodes 1081 h, 1081 kand/or first and second electrodes 1098, 1099, include one or more canelectrodes 1081 a, 1081 b, 1081 c.

Recording and monitoring systems and methods that may benefit fromcardiac activation sequence monitoring and tracking in accordance withthe present invention are further described in commonly assignedco-pending US Publication No. 2005/0004615, which is hereby incorporatedherein by reference.

Electrodes may also be provided on the back of the can 1003, typicallythe side facing externally relative to the patient after implantation.For example, electrodes 1081 m, 1081 p, and 1081 r are illustrated aspositioned in or on the back of the can 1003. Providing electrodes onboth front and back surfaces of the can 1003 provides for athree-dimensional spatial distribution of the electrodes, which mayprovide additional discrimination capabilities for cardiac activationsequence monitoring and tracking in accordance with the presentinvention. Further description of three-dimensional configurations aredescribed in U.S. Pat. No. 7,299,086 previously incorporated herein byreference.

In this and other configurations, the header 1089 incorporates interfacefeatures (e.g., electrical connectors, ports, engagement features, andthe like) that facilitate electrical connectivity with one or more leadand/or sensor systems, lead and/or sensor modules, and electrodes. Theheader 1089 may also incorporate one or more electrodes in addition to,or instead of, the electrodes provided by the lead 1083, such aselectrodes 1081 h and 1081 k, to provide more available vectors to thePIMD. The interface features of the header 1089 may be protected frombody fluids using known techniques.

The PIMD 1082 may further include one or more sensors in or on the can1003, header 1089, electrode module 1096, or lead(s) that couple to theheader 1089 or electrode module 1096. Useful sensors may includeelectrophysiologic and non-electrophysiologic sensors, such as anacoustic sensor, an impedance sensor, a blood sensor, such as an oxygensaturation sensor (oximeter or plethysmographic sensor), a bloodpressure sensor, minute ventilation sensor, or other sensor described orincorporated herein.

In one configuration, as is illustrated in FIG. 11, electrode subsystemsof a PIMD system are arranged about a patient's heart 1110. The PIMDsystem includes a first electrode subsystem, including a can electrode1102, and a second electrode subsystem 1104 that includes at least twoelectrodes or at least one multi-element electrode. The second electrodesubsystem 1104 may include a number of electrodes used for sensingand/or electrical stimulation and is connected to pulse generator 905via lead 1106.

In various configurations, the second electrode subsystem 1104 mayinclude a combination of electrodes. The combination of electrodes ofthe second electrode subsystem 1104 may include coil electrodes, tipelectrodes, ring electrodes, multi-element coils, spiral coils, spiralcoils mounted on non-conductive backing, screen patch electrodes, andother electrode configurations as will be described below. A suitablenon-conductive backing material is silicone rubber, for example.

The can electrode 1102 is positioned on the housing 1101 that enclosesthe PIMD electronics. In one embodiment, the can electrode 1102 includesthe entirety of the external surface of housing 1101. In otherembodiments, various portions of the housing 1101 may be electricallyisolated from the can electrode 1102 or from tissue. For example, theactive area of the can electrode 1102 may include all or a portion ofeither the anterior or posterior surface of the housing 1101 to directcurrent flow in a manner advantageous for cardiac sensing and/orstimulation.

Portions of the housing may be electrically isolated from tissue tooptimally direct current flow. For example, portions of the housing 1101may be covered with a non-conductive, or otherwise electricallyresistive, material to direct current flow. Suitable non-conductivematerial coatings include those formed from silicone rubber,polyurethane, or parylene, for example.

FIG. 12 is a block diagram depicting various componentry of differentarrangements of a PIMD in accordance with embodiments of the presentinvention. The components, functionality, and configurations depicted inFIG. 12 are intended to provide an understanding of various features andcombinations of features that may be incorporated in a PIMD. It isunderstood that a wide variety of device configurations arecontemplated, ranging from relatively sophisticated to relatively simpledesigns. As such, particular PIMD configurations may include somecomponentry illustrated in FIG. 12, while excluding other componentryillustrated in FIG. 12.

Illustrated in FIG. 12 is a processor-based control system 1205 whichincludes a micro-processor 1206 coupled to appropriate memory (volatileand/or non-volatile) 1209, it being understood that any logic-basedcontrol architecture may be used. The control system 1205 is coupled tocircuitry and components to sense, detect, and analyze electricalsignals produced by the heart and deliver electrical stimulation energyto the heart under predetermined conditions to treat cardiac arrhythmiasand/or other cardiac conditions. The control system 1205 and associatedcomponents also provide pacing therapy to the heart. The electricalenergy delivered by the PIMD may be in the form of low energy pacingpulses or high-energy pulses for cardioversion or defibrillation.

Cardiac signals are sensed using the electrode(s) 1214 and the can orindifferent electrode 1207 provided on the PIMD housing. Cardiac signalsmay also be sensed using only the electrode(s) 1214, such as in anon-active can configuration. As such, unipolar, bipolar, or combinedunipolar/bipolar electrode configurations as well as multi-elementelectrodes and combinations of noise canceling and standard electrodesmay be employed. The sensed cardiac signals are received by sensingcircuitry 1204, which includes sense amplification circuitry and mayalso include filtering circuitry and an analog-to-digital (ND)converter. The sensed cardiac signals processed by the sensing circuitry1204 may be received by noise reduction circuitry 1203, which mayfurther reduce noise before signals are sent to the detection circuitry1202.

Noise reduction circuitry 1203 may also be incorporated after sensingcircuitry 1204 in cases where high power or computationally intensivenoise reduction algorithms are required. The noise reduction circuitry1203, by way of amplifiers used to perform operations with the electrodesignals, may also perform the function of the sensing circuitry 1204.Combining the functions of sensing circuitry 1204 and noise reductioncircuitry 1203 may be useful to minimize the necessary componentry andlower the power requirements of the system.

In the illustrative configuration shown in FIG. 12, the detectioncircuitry 1202 is coupled to, or otherwise incorporates, noise reductioncircuitry 1203. The noise reduction circuitry 1203 operates to improvethe SNR of sensed cardiac signals by removing noise content of thesensed cardiac signals introduced from various sources. Typical types ofcardiac signal noise include electrical noise and noise produced fromskeletal muscles, for example. A number of methodologies for improvingthe SNR of sensed cardiac signals in the presence of skeletal muscularinduced noise, including signal separation techniques incorporatingcombinations of electrodes and multi-element electrodes, are describedhereinbelow.

Detection circuitry 1202 may include a signal processor that coordinatesanalysis of the sensed cardiac signals and/or other sensor inputs todetect cardiac arrhythmias, such as, in particular, tachyarrhythmia.Rate based and/or morphological discrimination algorithms may beimplemented by the signal processor of the detection circuitry 1202 todetect and verify the presence and severity of an arrhythmic episode.Examples of arrhythmia detection and discrimination circuitry,structures, and techniques, aspects of which may be implemented by aPIMD of a type that may benefit from cardiac activation sequencemonitoring and/or tracking methods and implementations are disclosed incommonly owned U.S. Pat. Nos. 5,301,677, 6,438,410, and 6,708,058, whichare hereby incorporated herein by reference. Arrhythmia detectionmethodologies particularly well suited for implementation in cardiacmonitoring and/or stimulation systems are described hereinbelow.

The detection circuitry 1202 communicates cardiac signal information tothe control system 1205. Memory circuitry 1209 of the control system1205 contains parameters for operating in various monitoring,defibrillation, and, if applicable, pacing modes, and stores dataindicative of cardiac signals received by the detection circuitry 1202.The memory circuitry 1209 may also be configured to store historical ECGand therapy data, which may be used for various purposes and transmittedto an external receiving device as needed or desired.

In certain configurations, the PIMD may include diagnostics circuitry1210. The diagnostics circuitry 1210 typically receives input signalsfrom the detection circuitry 1202 and the sensing circuitry 1204. Thediagnostics circuitry 1210 provides diagnostics data to the controlsystem 1205, it being understood that the control system 1205 mayincorporate all or part of the diagnostics circuitry 1210 or itsfunctionality. The control system 1205 may store and use informationprovided by the diagnostics circuitry 1210 for a variety of diagnosticspurposes. This diagnostic information may be stored, for example,subsequent to a triggering event or at predetermined intervals, and mayinclude system diagnostics, such as power source status, therapydelivery history, and/or patient diagnostics. The diagnostic informationmay take the form of electrical signals or other sensor data acquiredimmediately prior to therapy delivery.

According to a configuration that provides cardioversion anddefibrillation therapies, the control system 1205 processes cardiacsignal data received from the detection circuitry 1202 and initiatesappropriate tachyarrhythmia therapies to terminate cardiac arrhythmicepisodes and return the heart to normal sinus rhythm. The control system1205 is coupled to shock therapy circuitry 1216. The shock therapycircuitry 1216 is coupled to the electrode(s) 1214 and the can orindifferent electrode 1207 of the PIMD housing.

Upon command, the shock therapy circuitry 1216 delivers cardioversionand defibrillation stimulation energy to the heart in accordance with aselected cardioversion or defibrillation therapy. In a lesssophisticated configuration, the shock therapy circuitry 1216 iscontrolled to deliver defibrillation therapies, in contrast to aconfiguration that provides for delivery of both cardioversion anddefibrillation therapies. Examples of PIMD high energy deliverycircuitry, structures and functionality, aspects of which may beincorporated in a PIMD of a type that may benefit from aspects of thepresent invention are disclosed in commonly owned U.S. Pat. Nos.5,372,606; 5,411,525; 5,468,254; and 5,634,938, which are herebyincorporated herein by reference.

Arrhythmic episodes may also be detected and verified bymorphology-based analysis of sensed cardiac signals as is known in theart. Tiered or parallel arrhythmia discrimination algorithms may also beimplemented using both rate-based and morphologic-based approaches.Further, a rate and pattern-based arrhythmia detection anddiscrimination approach may be employed to detect and/or verifyarrhythmic episodes, such as the approach disclosed in U.S. Pat. Nos.6,487,443; 6,259,947; 6,141,581; 5,855,593; and 5,545,186, which arehereby incorporated herein by reference.

In accordance with another configuration, a PIMD may incorporate acardiac pacing capability in addition to, or to the exclusion of,cardioversion and/or defibrillation capabilities. As is shown in FIG.12, the PIMD includes pacing therapy circuitry 1230 that is coupled tothe control system 1205 and the electrode(s) 1214 and can/indifferentelectrodes 1207. Upon command, the pacing therapy circuitry 1230delivers pacing pulses to the heart in accordance with a selected pacingtherapy.

Control signals, developed in accordance with a pacing regimen bypacemaker circuitry within the control system 1205, are initiated andtransmitted to the pacing therapy circuitry 1230 where pacing pulses aregenerated. A pacing regimen, such as those discussed and incorporatedherein, may be modified by the control system 1205. In one particularapplication, a sense vector optimization approach of the presentinvention may be implemented to enhance capture detection and/or capturethreshold determinations, such as by selecting an optimal vector forsensing an evoked response resulting from application of a capturepacing stimulus.

The PIMD shown in FIG. 12 may be configured to receive signals from oneor more physiologic and/or non-physiologic sensors. Depending on thetype of sensor employed, signals generated by the sensors may becommunicated to transducer circuitry coupled directly to the detectioncircuitry 1202 or indirectly via the sensing circuitry 1204. It is notedthat certain sensors may transmit sense data to the control system 1205without processing by the detection circuitry 1202.

Communications circuitry 1218 is coupled to the microprocessor 1206 ofthe control system 1205. The communications circuitry 1218 allows thePIMD to communicate with one or more receiving devices or systemssituated external to the PIMD. By way of example, the PIMD maycommunicate with a patient-worn, portable or bedside communicationsystem via the communications circuitry 1218. In one configuration, oneor more physiologic or non-physiologic sensors (subcutaneous, cutaneous,or external of patient) may be equipped with a short-range wirelesscommunication interface, such as an interface conforming to a knowncommunications standard, such as Bluetooth or IEEE 802 standards. Dataacquired by such sensors may be communicated to the PIMD via thecommunications circuitry 1218. It is noted that physiologic ornon-physiologic sensors equipped with wireless transmitters ortransceivers may communicate with a receiving system external of thepatient.

The communications circuitry 1218 allows the PIMD to communicate with anexternal programmer. In one configuration, the communications circuitry1218 and the programmer unit (not shown) use a wire loop antenna and aradio frequency telemetric link, as is known in the art, to receive andtransmit signals and data between the programmer unit and communicationscircuitry 1218. In this manner, programming commands and data aretransferred between the PIMD and the programmer unit during and afterimplant. Using a programmer, a physician is able to set or modifyvarious parameters used by the PIMD. For example, a physician may set ormodify parameters affecting monitoring, detection, pacing, anddefibrillation functions of the PIMD, including pacing andcardioversion/defibrillation therapy modes.

Typically, the PIMD is encased and hermetically sealed in a housingsuitable for implanting in a human body as is known in the art. Power tothe PIMD is supplied by an electrochemical power source 1220 housedwithin the PIMD. In one configuration, the power source 1220 includes arechargeable battery. According to this configuration, chargingcircuitry is coupled to the power source 1220 to facilitate repeatednon-invasive charging of the power source 1220. The communicationscircuitry 1218, or separate receiver circuitry, is configured to receiveRF energy transmitted by an external RF energy transmitter. The PIMDmay, in addition to a rechargeable power source, include anon-rechargeable battery. It is understood that a rechargeable powersource need not be used, in which case a long-life non-rechargeablebattery is employed.

The detection circuitry 1202, which is coupled to a microprocessor 1206,may be configured to incorporate, or communicate with, specializedcircuitry for processing sensed cardiac signals in manners particularlyuseful in a cardiac sensing and/or stimulation device. As is shown byway of example in FIG. 12, the detection circuitry 1202 may receiveinformation from multiple physiologic and non-physiologic sensors.

The detection circuitry 1202 may also receive information from one ormore sensors that monitor skeletal muscle activity. In addition tocardiac activity signals, electrodes readily detect skeletal musclesignals. Such skeletal muscle signals may be used to determine theactivity level of the patient. In the context of cardiac signaldetection, such skeletal muscle signals are considered artifacts of thecardiac activity signal, which may be viewed as noise.

The components, functionality, and structural configurations depictedherein are intended to provide an understanding of various features andcombination of features that may be incorporated in a PIMD. It isunderstood that a wide variety of PIMDs and other implantable cardiacmonitoring and/or stimulation device configurations are contemplated,ranging from relatively sophisticated to relatively simple designs. Assuch, particular PIMD or cardiac monitoring and/or stimulation deviceconfigurations may include particular features as described herein,while other such device configurations may exclude particular featuresdescribed herein.

The PIMD may detect a variety of physiological signals that may be usedin connection with various diagnostic, therapeutic or monitoringimplementations. For example, the PIMD may include sensors or circuitryfor detecting respiratory system signals, cardiac system signals, andsignals related to patient activity. In one embodiment, the PIMD sensesintrathoracic impedance, from which various respiratory parameters maybe derived, including, for example, respiratory tidal volume and minuteventilation. Sensors and associated circuitry may be incorporated inconnection with a PIMD for detecting one or more body movement or bodyposture or position related signals. For example, accelerometers and GPSdevices may be employed to detect patient activity, patient location,body orientation, or torso position.

Referring now to FIG. 13, a PIMD of the present invention may be usedwithin the structure of an advanced patient management (APM) system1300. The advanced patient management system 1300 allows physicians toremotely and automatically monitor cardiac and respiratory functions, aswell as other patient conditions. In one example, a PIMD implemented asa cardiac pacemaker, defibrillator, or resynchronization device may beequipped with various telecommunications and information technologiesthat enable real-time data collection, diagnosis, and treatment of thepatient. Various PIMD embodiments described herein may be used inconnection with advanced patient management. Methods, structures, and/ortechniques described herein, which may be adapted to provide for remotepatient/device monitoring, diagnosis, therapy, or other APM relatedmethodologies, may incorporate features of one or more of the followingreferences: U.S. Pat. Nos. 6,221,011; 6,270,457; 6,277,072; 6,280,380;6,312,378; 6,336,903; 6,358,203; 6,368,284; 6,398,728; and 6,440,066,which are hereby incorporated herein by reference.

As is illustrated in FIG. 13, the medical system 1300 may be used toimplement coordinated patient measuring and/or monitoring, diagnosis,and/or therapy in accordance with embodiments of the invention. Themedical system 1300 may include, for example, one or morepatient-internal medical devices 1310, such as a PIMD, and one or morepatient-external medical devices 1320, such as a monitor or signaldisplay device. Each of the patient-internal 1310 and patient-external1320 medical devices may include one or more of a patient monitoringunit 1312, 1322, a diagnostics unit 1314, 1324, and/or a therapy unit1316, 1326.

The patient-external medical device 1320 performs monitoring, and/ordiagnosis and/or therapy functions external to the patient (i.e., notinvasively implanted within the patient's body). The patient-externalmedical device 1320 may be positioned on the patient, near the patient,or in any location external to the patient.

The patient-internal and patient-external medical devices 1310, 1320 maybe coupled to one or more sensors 1341, 1342, 1345, 1346, patientinput/trigger devices 1343, 1347 and/or other information acquisitiondevices 1344, 1348. The sensors 1341, 1342, 1345, 1346, patientinput/trigger devices 1343, 1347, and/or other information acquisitiondevices 1344, 1348 may be employed to detect conditions relevant to themonitoring, diagnostic, and/or therapeutic functions of thepatient-internal and patient-external medical devices 1310, 1320.

The medical devices 1310, 1320 may each be coupled to one or morepatient-internal sensors 1341, 1345 that are fully or partiallyimplantable within the patient. The medical devices 1310, 1320 may alsobe coupled to patient-external sensors positioned on, near, or in aremote location with respect to the patient. The patient-internal andpatient-external sensors are used to sense conditions, such asphysiological or environmental conditions, that affect the patient.

The patient-internal sensors 1341 may be coupled to the patient-internalmedical device 1310 through one or more internal leads 1353. Stillreferring to FIG. 13, one or more patient-internal sensors 1341 may beequipped with transceiver circuitry to support wireless communicationsbetween the one or more patient-internal sensors 1341 and thepatient-internal medical device 1310 and/or the patient-external medicaldevice 1320.

The patient-external sensors 1342 may be coupled to the patient-internalmedical device 1310 and/or the patient-external medical device 1320through one or more internal leads 1355 or through wireless connections.Patient-external sensors 1342 may communicate with the patient-internalmedical device 1310 wirelessly. Patient-external sensors 1342 may becoupled to the patient-external medical device 1320 through one or moreinternal leads 1357 or through a wireless link.

In an embodiment of the present invention, the patient-external medicaldevice 1320 includes a visual display configured to concurrently displaynon-electrophysiological signals and ECG signals. For example, thedisplay may present the information visually. The patient-externalmedical device 1320 may also, or alternately, provide signals to othercomponents of the medical system 1300 for presentation to a clinician,whether local to the patient or remote to the patient.

Referring still to FIG. 13, the medical devices 1310, 1320 may beconnected to one or more information acquisition devices 1344, 1348,such as a database that stores information useful in connection with themonitoring, diagnostic, or therapy functions of the medical devices1310, 1320. For example, one or more of the medical devices 1310, 1320may be coupled through a network to a patient information server 1330.

The input/trigger devices 1343, 1347 are used to allow the physician,clinician, and/or patient to manually trigger and/or transferinformation to the medical devices 1310, 1320. The input/trigger devices1343, 1347 may be particularly useful for inputting informationconcerning patient perceptions, such as a perceived cardiac event, howwell the patient feels, and other information not automatically sensedor detected by the medical devices 1310, 1320. For example, the patientmay trigger the input/trigger device 1343 upon perceiving a cardiacevent. The trigger may then initiate the recording of cardiac signalsand/or other sensor signals in the patient-internal device 1310. Later,a clinician may trigger the input/trigger device 1347, initiating thetransfer of the recorded cardiac and/or other signals from thepatient-internal device 1310 to the patient-external device 1320 fordisplay and diagnosis. The input/trigger device 1347 may also be used bythe patient, clinician, and/or physician as an activation stimulus tothe PIMD to update and/or select a vector.

In one embodiment, the patient-internal medical device 1310 and thepatient-external medical device 1320 may communicate through a wirelesslink between the medical devices 1310, 1320. For example, thepatient-internal and patient-external devices 1310, 1320 may be coupledthrough a short-range radio link, such as Bluetooth, IEEE 802.11, and/ora proprietary wireless protocol. The communications link may facilitateuni-directional or bi-directional communication between thepatient-internal 1310 and patient-external 1320 medical devices. Dataand/or control signals may be transmitted between the patient-internal1310 and patient-external 1320 medical devices to coordinate thefunctions of the medical devices 1310, 1320.

In another embodiment, patient data may be downloaded from one or moreof the medical devices periodically or on command, and stored at thepatient information server 1330. The physician and/or the patient maycommunicate with the medical devices and the patient information server1330, for example, to acquire patient data or to initiate, terminate ormodify recording and/or therapy.

The data stored on the patient information server 1330 may be accessibleby the patient and the patient's physician through one or more terminals1350, e.g., remote computers located in the patient's home or thephysician's office. The patient information server 1330 may be used tocommunicate to one or more of the patient-internal and patient-externalmedical devices 1310, 1320 to provide remote control of the monitoring,diagnosis, and/or therapy functions of the medical devices 1310, 1320.

In one embodiment, the patient's physician may access patient datatransmitted from the medical devices 1310, 1320 to the patientinformation server 1330. After evaluation of the patient data, thepatient's physician may communicate with one or more of thepatient-internal or patient-external devices 1310, 1320 through an APMsystem 1340 to initiate, terminate, or modify the monitoring,diagnostic, and/or therapy functions of the patient-internal and/orpatient-external medical systems 1310, 1320.

In another embodiment, the patient-internal and patient-external medicaldevices 1310, 1320 may not communicate directly, but may communicateindirectly through the APM system 1340. In this embodiment, the APMsystem 1340 may operate as an intermediary between two or more of themedical devices 1310, 1320. For example, data and/or control informationmay be transferred from one of the medical devices 1310, 1320 to the APMsystem 1340. The APM system 1340 may transfer the data and/or controlinformation to another of the medical devices 1310, 1320.

In one embodiment, the APM system 1340 may communicate directly with thepatient-internal and/or patient-external medical devices 1310, 1320. Inanother embodiment, the APM system 1340 may communicate with thepatient-internal and/or patient-external medical devices 1310, 1320through medical device programmers 1360, 1370 respectively associatedwith each medical device 1310, 1320. As was stated previously, thepatient-internal medical device 1310 may take the form of an implantablePIMD.

In accordance with one approach of the present invention, a PIMD may beimplemented to separate cardiac signals for selection and monitoring ofvectors in a robust manner using a blind source separation (BSS)technique. It is understood that all or certain aspects of the BSStechnique described below may be implemented in a device or system(implantable or non-implantable) other than a PIMD, and that thedescription of BSS techniques implemented in a PIMD is provided forpurposes of illustration, and not of limitation. For example, algorithmsthat implement a BSS technique as described below may be implemented foruse by an implanted processor or a non-implanted processor, such as aprocessor of a programmer or computer of a patient-external devicecommunicatively coupled to the PIMD.

Referring now to FIGS. 14 through 16, cardiac monitoring and/orstimulation devices and methods employing cardiac signal separation aredescribed in accordance with the present invention. The PIMD may beimplemented to separate signal components according to their sources andproduce one or more cardiac signal vectors associated with all or aportion of one or more cardiac activation sequences based on the sourceseparation. To achieve this, the methods and algorithms illustrated inFIGS. 14 through 16 may be implemented.

FIG. 14 illustrates a portion of a cardiac activation sequencemonitoring and/or tracking system 1425 in accordance with the presentinvention. A process 1414 is performed, providing a selected vector 1419along with vector information including, for example, magnitude, angle,rates of change, trend information, and other statistics. The selectedvector 1419 (and associated signal and other vector information) isavailable for a variety of uses 1420, such as, for example, arrhythmiadiscrimination, therapy titration, posture detection/monitoring,ischemia detection/monitoring, capture verification, disease diagnosisand/or progress information, or other use. In accordance with thepresent invention, the process may be used, and repeated, to monitorcardiac activation sequences, track changes in the progression ofpatient pathology, and to update sense vectors useful for cardiacsensing and/or stimulation, for example.

FIG. 15 illustrates an embodiment of a signal source separation/updateprocess 1500 useful for cardiac activation sequence monitoring and/ortracking in accordance with the present invention. A set of compositesignals, including at least two and up to n signals, are selected forseparation, where n is an integer. Each electrode provides a compositesignal associated with an unknown number of sources. Pre-processingand/or pre-filtering 1612 may be performed on each of the compositesignals. It may be advantageous to filter each composite signal usingthe same filtering function. Source separation 1614 is performed,providing at least one separated signal. If a treatment is desired, anappropriate treatment or therapy 1618 is performed. If continued sourceseparation is desired, the process returns to perform such sourceseparation 1614 and may iteratively separate 1616 more signals until adesired signal is found, or all signals are separated.

The separated signal or signals may then be used 1620 for some specifiedpurpose, such as, for example, to confirm a normal sinus rhythm,determine a cardiac condition, define a noise signal, monitor cardiacactivation sequence, determine patient posture, diagnose or monitor adisease state, or other desired use. Electrode arrays and/or the use ofmultiple electrodes provide for many possible vectors useful for sensingcardiac activity.

Updating the vector to monitor and/or track changes may be performedperiodically, on demand, at a predetermined time, upon the occurrence ofa predetermined event, continuously, or as otherwise desired. Forexample, a PIMD may regularly perform an update of the sense vector usedfor cardiac discrimination, to keep performance of the PIMD improvedand/or adjusted and/or optimized and/or to track or monitor progressionof changes. Updating may be useful, for example, when pathology,therapy, posture, or other system or patient change suggests a change invector may be detected and/or useful.

For example, in an APM environment such as described previously, a PIMDin accordance with the present invention may have a controller andcommunications circuitry that transmits its cardiac composite signals toa bedside signal processor when the patient is asleep. The signalprocessor may perform a blind source separation and analysis of thecomposite signals during the patient's sleep cycle. The signal processormay then determine the appropriate vector or vectors for the PIMD, andreprogram the PIMD before the patient awakes. The PIMD may then operatewith the latest programming until the next update.

FIG. 16 illustrates further embodiments of a signal source separationprocess in greater detail, including some optional elements. Entry ofthe process at block 1622 provides access to a pre-processing facility1612, illustrated here as including a covariance matrix computationblock 1624 and/or a pre-filtering block 1626 such as, for example, aband-pass filtering block. The composite signals processed atpre-processing block 1612 are provided to a signal source separationblock 1615, which may include functionality of the source separationblock 1614 and iterative source separation block 1616 shown in FIG. 15.

The signal source separation block 1615 includes a principal componentanalysis block 1628, which produces an associated set of eigenvectorsand eigenvalues using a covariance matrix or composite signals providedby pre-processing block 1612. A determination 1630 is made as to whetherone eigenvalue is significantly larger than any others in the set,making the dimension associated with this eigenvalue a likely candidatefor association with the direction along which the power of the signalis maximized. If such a candidate is identified at block 1630, thecandidate signal may immediately be separated 1631 and a determination1633 made to confirm whether the candidate signal is a cardiac signal,before returning 1644 to the master PIMD routine that called the signalsource separation process.

If there is no clear candidate eigenvalue, or if the largest valueeigenvalue did not provide a signal of interest, an iterative processmay be used to separate 1632 and search 1636 for the signal of interest(e.g., cardiac signal). This process 1632, 1636, 1634 may be repeateduntil such a signal is found, or no more signals are separable 1634 asdetermined by exceeding a predefined number of iterations N_(max) orsome other termination criterion. An example of such a criterion is aneigenvalue considered at the current iteration being proportionatelysmaller than the largest eigenvalues by some predetermined amount.

If the iterations 1634 are completed and a cardiac signal is not foundat 1636, then an Independent component analysis 1635 may be attempted tofurther process the signals in an attempt to find the cardiac signal. Ifa cardiac signal is still not found at decision 1637, after exhaustingall possibilities, then a set of default settings 1639 may be used, oran error routine may be initiated.

In another embodiment of the present invention, a method of signalseparation involves sensing, at least in part implantably, two or morecomposite signals using three or more cardiac electrodes or electrodearray elements. The method may further involve performing a sourceseparation using the detected composite signals, the source separationproducing two or more vectors. A first vector and a second vector may beselected from the set of vectors.

The use of the terms first and second vector are not intended to implythat the vectors are the first and second vectors separated from thecomposite signal, but that a first vector and a second vector areselected from among any vectors available for a given composite signal.First and second signals may be identified from the detected two or morecomposite signals using the first and second vectors respectively. Themethod then involves selecting either the first vector or the secondvector as a selected vector based on a selection criterion.

Selection criteria may include finding the optimum vector for cardiacsignal identification, finding a vector that provides the largestmagnitude cardiac signal, or finding another particular signal ofinterest. For example, the first vector may be selected and used forcardiac activity monitoring, and the second vector may then be selectedand used for skeletal muscle activity monitoring. The skeletal musclesignal may then be used to further discriminate arrhythmias from noisesuch as is further described in commonly owned U.S. Pat. No. 7,117,035,which is hereby incorporated herein by reference.

With continued reference to FIGS. 14 through 16, one illustrative signalsource separation methodology useful with the present invention isdescribed below. Such an approach is particularly well suited for use ina PIMD system. It is to be understood that the example provided below isprovided for non-limiting, illustrative purposes only. Moreover, it isunderstood that signal source separation within the context of thepresent invention need not be implemented using the specific processesdescribed below, or each and every process described below.

A collected signal may be pre-filtered to suppress broadly incoherentnoise and to generally optimize the signal-to-noise ratio (SNR). Anynoise suppression in this step has the additional benefit of reducingthe effective number of source signals that need to be separated. APrincipal Component Analysis (PCA) may be performed on the collectedand/or pre-filtered signal, producing a set of eigenvectors andassociated eigenvalues describing the optimal linear combination, in aleast-squares sense, of the recorded signals that makes the componentscoming from different sources orthogonal to one another. As anintermediate step to performing the PCA, an estimate of the spatialcovariance matrix may be computed and averaged over a relatively shorttime interval (on the order of 2-3 beats), or over the windowed signalas described previously, to enhance those components that are mutuallycorrelated.

Each eigenvalue corresponds to the power of the signal projected alongthe direction of each associated eigenvector. The cardiac signalcomponent is typically identified by one of the largest eigenvalues.Occasionally, PCA does not achieve a substantially sufficient level ofsource independence. In such a case, an Independent Component Analysis(ICA) may be performed to determine the actual source direction, eitherupon the PCA-transformed signal, or directly upon the collected signal.The ICA consists of a unitary transformation based on higher-orderstatistical analysis.

For example, separation of two mixed sources may be achieved by rotatingthe complex variable formed from the signals on an angle that alignstheir probability distributions with basis vectors. In another approach,an algorithm based on minimization of mutual information betweencomponents, as well as other approaches generally known in the field ofICA, may be used to achieve reconstructed source independence.

A PIMD may, for example, employ a hierarchical decision-making procedurethat initiates a blind source separation algorithm upon the detection ofa condition under which the target vector may change. By way of example,a local peak density algorithm or a curvature-based significant pointmethodology may be used as a high-level detection routine. Othersensors/information available to the PIMD may also trigger theinitiation of a blind source separation algorithm.

The PIMD may compute an estimate of the covariance matrix. It may besufficient to compute the covariance matrix for only a short time.Computation of the eigenvalues and eigenvectors required for the PCA mayalso be performed adaptively through an efficient updating algorithm.

The cardiac signal may be identified among the few (e.g., two or three)largest separated signals. One of several known algorithms may be used.For example, local peak density (LPD) or beat detection (BD) algorithmsmay be used. The LPD algorithm may be used to identify the cardiacsignal by finding a signal that has an acceptable physiologic range oflocal peak densities by comparing the LPD to a predetermined range ofpeak densities known to be acceptable. The BD algorithm finds a signalthat has a physiologic range of beat rate. In the case where two signalslook similar, a morphology algorithm may be used for furtherdiscrimination. It may be beneficial to use the same algorithm atdifferent levels of hierarchy: 1) initiation of blind source separationalgorithm; 2) iterative identification of a cardiac signal.

Mathematical development of an example of blind source separationalgorithm in accordance with the present invention is provided asfollows. Assume there are m source signals s₁(t), . . . , s_(m)(t) thatare detected inside of the body, including a desired cardiac signal andsome other independent noise, which may, for example, includemyopotential noise, electrocautery response, etc. These signals arerecorded simultaneously from k sensing vectors derived from subcutaneoussensing electrodes, where all m signals may be resolved if k>m. Bydefinition, the signals are mixed together into the overall voltagegradient sensed across the electrode array. In addition, there isusually an additive noise attributable, for example, to environmentalnoise sources. The relationship between the source signals s(t) andrecorded signals x(t) is described below:

${{\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\M \\{x_{k}(t)}\end{pmatrix} = {{\begin{pmatrix}{y_{1}(t)} \\{y_{2}(t)} \\M \\{y_{k}(t)}\end{pmatrix} + \begin{pmatrix}{n_{1}(t)} \\{n_{2}(t)} \\M \\{n_{k}(t)}\end{pmatrix}} = {{{\begin{pmatrix}a_{11} & a_{12} & \ldots & a_{1\; m} \\a_{21} & a_{22} & \ldots & a_{2\; m} \\M & M & O & M \\a_{k\; 1} & a_{k\; 2} & \ldots & a_{k\; m}\end{pmatrix}\begin{pmatrix}{s_{1}(t)} \\{s_{2}(t)} \\M \\{s_{m}(t)}\end{pmatrix}} + \begin{pmatrix}{n_{1}(t)} \\{n_{2}(t)} \\M \\{n_{k}(t)}\end{pmatrix}} = {{x(t)} = {{{y(t)} + {n(t)}} = {{{As}(t)} + {n(t)}}}}}}},\mspace{79mu}{m < k}}\mspace{56mu}$

Here, x(t) is an instantaneous linear mixture of the source signals andadditive noise, y(t) is the same linear mixture without the additivenoise, n(t) is environmental noise modeled as Gaussian noise, A is anunknown mixing matrix, and s(t) are the unknown source signalsconsidered here to include the desired cardiac signal and otherbiological artifacts. There is no assumption made about the underlyingstructure of the mixing matrix and the source signals, except for theirspatial statistical independence. The objective is to reconstruct thesource signals s(t) from the recorded signals x(t).

Reconstruction of the source signals s(t) from the recorded signals x(t)may involve pre-filtering x(t) to optimize the SNR (i.e., maximize thepower of s(t) against that of n(t)). Here, a linear phase filter may beused to minimize time-domain dispersion (tails and ringing) and bestpreserve the underlying cardiac signal morphology. It is noted that thenotation x(t) is substituted for the pre-filtered version of x(t).

An estimate of the spatial covariance matrix R is formed as shownimmediately below. This step serves to enhance the components of thesignal that are mutually correlated and downplays incoherent noise.

$R = {{\frac{1}{T_{({{\sim 1}\mspace{11mu}\sec})}}{\sum\limits_{{t = 1},T}{\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\\ldots \\{x_{k}(t)}\end{pmatrix}*\begin{pmatrix}{x_{1}(t)} & {x_{2}(t)} & \ldots & {x_{k}(t)}\end{pmatrix}}}} = {\frac{1}{T_{({{\sim 1}\mspace{11mu}\sec})}}{\sum\limits_{{t = 1},T}\begin{bmatrix}{{x_{1}(t)}*{x_{1}(t)}} & {{x_{1}(t)}*{x_{2}(t)}} & \ldots & {{x_{1}(t)}*{x_{k}(t)}} \\{{x_{2}(t)}*{x_{1}(t)}} & {{x_{2}(t)}*{x_{2}(t)}} & \ldots & {{x_{2}(t)}*{x_{k}(t)}} \\\ldots & \ldots & O & \ldots \\{{x_{k}(t)}*{x_{1}(t)}} & {{x_{k}(t)}*{x_{2}(t)}} & \ldots & {{x_{k}(t)}*{x_{k}(t)}}\end{bmatrix}}}}$

Eigenvalues and eigenvectors of the covariance matrix R may bedetermined using singular value decomposition (SVD). By definition, theSVD factors R as a product of three matrices R=USV^(T), where U and Vare orthogonal matrices describing amplitude preserving rotations, and Sis a diagonal matrix that has the squared eigenvalues σ₁ . . . σ_(k) onthe diagonal in monotonically decreasing order. Expanded into elements,this SVD may be expressed as follows.

$R = {\begin{pmatrix}u_{11} & u_{12} & \ldots & u_{1k} \\u_{21} & u_{22} & \ldots & u_{2k} \\M & M & O & M \\u_{k\; 1} & u_{k\; 2} & \ldots & u_{kk}\end{pmatrix}\begin{pmatrix}\sigma_{1} & 0 & 0 & 0 \\0 & \sigma_{2} & 0 & 0 \\M & M & O & M \\0 & 0 & K & \sigma_{k}\end{pmatrix}\begin{pmatrix}v_{11} & v_{12} & \ldots & v_{1k} \\v_{21} & v_{22} & \ldots & v_{2k} \\M & M & O & M \\v_{k\; 1} & v_{k\; 2} & \ldots & v_{kk}\end{pmatrix}}$

The columns of matrix V consist of eigenvectors that span a newcoordinate system wherein the components coming from different sourcesare orthogonal to one another. Eigenvalues σ₁ . . . σ_(k) correspondrespectively to columns 1 . . . k of V. Each eigenvalue defines thesignal “power” along the direction of its corresponding eigenvector. Thematrix V thus provides a rotational transformation of x(t) into a spacewhere each separate component of x is optimally aligned, in aleast-squares sense, with a basis vector of that space.

The largest eigenvalues correspond to the highest power components,which typically represent the mixed source signals y₁(t), . . . ,y_(m)(t). The lower eigenvalues typically are associated with additivenoise n₁(t), . . . , n_(k-m)(t). Each eigenvector may then be viewed asan optimal linear operator on x that maximizes the power of thecorresponding independent signal component. As a result, the transformedsignal is found as:

${\hat{y}(t)} = {\begin{pmatrix}{{\hat{y}}_{1}(t)} \\M \\{{\hat{y}}_{m}(t)}\end{pmatrix} = {\begin{pmatrix}v_{11} & v_{21} & K & v_{k\; 1} \\M & M & O & M \\v_{1m} & v_{2m} & \ldots & v_{k\; m}\end{pmatrix}*\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\M \\{x_{k}(t)}\end{pmatrix}}}$

The component estimates ŷ₁(t), . . . , ŷ_(m)(t) of y₁(t), . . . ,y_(m)(t) are aligned with the new orthogonal system of coordinatesdefined by eigenvectors. As a result, they should be orthogonal to eachother and thus independent.

In an alternative implementation, eigenvalues and eigenvectors of thecovariance matrix R may be determined using eigenvalue decomposition(ED). By definition, the ED solves the matrix equation RV=SV so that Sis a diagonal matrix having the eigenvalues σ₁ . . . σ_(k) on thediagonal, in monotonically decreasing order, and so that matrix Vcontains the corresponding eigenvectors along its columns. The resultingeigenvalues and associated eigenvectors may be applied in similar mannerto those resulting from the SVD of covariance matrix R.

In an alternative implementation, eigenvalues and eigenvectors arecomputed directly from x(t) by forming a rectangular matrix X of ksensor signals collected during a time sECGent of interest, andperforming an SVD directly upon X. The matrix X and its decompositionmay be expressed as follows.

$X = {\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\M \\{x_{k}(t)}\end{pmatrix} = {\begin{pmatrix}{x_{1}( t_{1} )} & {x_{1}( t_{2} )} & K & {x_{1}( t_{T} )} \\{x_{2}( t_{1} )} & {x_{2}( t_{2} )} & \Lambda & {x_{2}( t_{T} )} \\M & M & O & M \\{x_{k}( t_{1} )} & {x_{k}( t_{2} )} & \Lambda & {x_{k}( t_{T} )}\end{pmatrix} = {U\; S\; V^{T}}}}$

Note that in cases where T>k, a so-called “economy-size” SVD may be usedto find the eigenvalues and eigenvectors efficiently. Such an SVD may beexpressed as follows, expanded into elements.

$X = {{U\; S\; V^{T}} = {\begin{pmatrix}u_{11} & u_{12} & \ldots & u_{1k} \\u_{21} & u_{22} & \ldots & u_{2k} \\M & M & O & M \\u_{k\; 1} & u_{k\; 2} & \ldots & u_{kk}\end{pmatrix}\begin{pmatrix}\sigma_{1} & 0 & K & 0 \\0 & \sigma_{2} & K & 0 \\M & M & O & M \\0 & 0 & K & \sigma_{k}\end{pmatrix}\begin{pmatrix}v_{11} & v_{12} & \ldots & v_{1k} \\v_{21} & v_{22} & \ldots & v_{2k} \\M & M & O & M \\v_{k\; 1} & v_{k\; 2} & \ldots & v_{kk}\end{pmatrix}}}$

A similar economy-sized SVD may also be used for the less typical casewhere k>T. The matrices S and V resulting from performing the SVD ofdata matrix X may be applied in the context of this present inventionidentically as the matrices S and V resulting from performing the SVD onthe covariance matrix R.

At this point, the mutual separation of ŷ₁(t), . . . , ŷ_(m)(t) would becompleted, based on the covariance statistics. Occasionally, informationfrom covariance is not sufficient to achieve source independence. Thishappens, for example, when the cardiac signal is corrupted withelectrocautery, which may cause perturbations from the linearly additivenoise model. In such a case, Independent Component Analysis (ICA) may beused to further separate the signals.

The ICA seeks to find a linear transformation matrix W that inverts themixing matrix A in such manner as to recover an estimate of the sourcesignals. The operation may be described as follows.

${s(t)} = {\begin{pmatrix}{s_{1}(t)} \\{s_{2}(t)} \\M \\{s_{m}(t)}\end{pmatrix} = {{{Wy}(t)} \approx {A^{- 1}{y(t)}}}}$

Here we substitute s(t) for the recovered estimate of the sourcesignals. The signal vector y(t) corresponds to either the collectedsensor signal vector x(t) or to the signal ŷ(t) separated with PCA. Thematrix W is the solution of an optimization problem that maximizes theindependence between the components s₁(t), . . . , s_(m)(t) ofs(t)=Wy(t). We treat the components of s(t) as a vector of randomvariables embodied in the vector notation s, so that the desiredtransformation would optimize some cost function C(s)=C([s₁(t), . . . ,s_(m)(t)]) that measures the mutual independence of these components.Given the joint probability density function (pdf) f(s) and thefactorized pdf f(s)=f₁(s)f₂(s₂) . . . f_(m)(s_(m)), or given estimatesof these pdf's, we may solve the following.

${\begin{matrix}\min \\W\end{matrix}{C(s)}} = {\begin{matrix}\min \\W\end{matrix}{\int{{D( {{f(s)},{\overset{\_}{f}(s)}} )}{\mathbb{d}s}}}}$

The function D(f(s), f(s)) may be understood as a standard distancemeasure generally known in the art, such as for example an absolutevalue difference |f(s)− f(s)|, Euclidean distance (f(s)− f(s))², orp-norm (f(s)− f(s))^(p). The distance measure approaches zero as f(s)approaches f(s), which by the definition of statistical independence,occurs as the components of s approach mutual statistical independence.

In an alternative implementation, the distance measure may take the formof a Kullback-Liebler divergence (KLD) between f(s) and f(s), yieldingcost function optimizations in either of the following forms.

$\begin{matrix}{{{\begin{matrix}\min \\W\end{matrix}{C(s)}} = {\begin{matrix}\min \\W\end{matrix}{\int{{f(s)}\log\frac{f(s)}{\overset{\_}{f}(s)}{\mathbb{d}s}\mspace{14mu}{or}}}}}\mspace{14mu}} \\{= {\begin{matrix}\min \\W\end{matrix}{\int{{\overset{\_}{f}(s)}\log\frac{\overset{\_}{f}(s)}{f(s)}{\mathbb{d}s}}}}}\end{matrix}$

Since the KLD is not symmetric, the two alternative measures are relatedbut not precisely equal. One measure could be chosen, for example, if aparticular underlying data distribution favors convergence with thatmeasure.

Several alternative approaches may be used to measure the mutualindependence of the components of s. These may include the maximumlikelihood method, maximization of negentropy or its approximation, andminimization of mutual information.

In the maximum likelihood method, the desired matrix W is found as asolution of the following optimization problem,

${{\max\limits_{W}{\sum\limits_{j = 1}^{T}{\sum\limits_{i = 1}^{m}{\log\mspace{11mu}{f_{i}( {s_{i}( t_{j} )} )}}}}} + {T\mspace{11mu}\log{{\det W}}}} = {{\max\limits_{W}{\sum\limits_{j = 1}^{T}{\sum\limits_{i = 1}^{m}{\log\mspace{11mu}{f_{i}( {w_{i}^{T}{y( t_{j} )}} )}}}}} + {T\mspace{11mu}\log{{\det W}}}}$

where w_(i) are columns of the matrix W. In the negentropy method, thecost function is defined in terms of differences in entropy between sand a corresponding Gaussian random variable, resulting in the followingoptimization problem,

${\max\limits_{W}\{ {{H( s_{gauss} )} - {H(s)}} \}} = {\max\limits_{W}\{ {{- {\int{{f( s_{gauss} )}\log\mspace{11mu}{f( s_{gauss} )}{\mathbb{d}s_{gauss}}}}} + {\int{{f(s)}{\log(s)}{\mathbb{d}s}}}} \}}$where H(s) is the entropy of random vector s, and s_(gauss) is aGaussian random vector chosen to have a covariance matrix substantiallythe same as that of s.

In the minimization of mutual information method, the cost function isdefined in terms of the difference between the entropy of s and the sumof the individual entropies of the components of s, resulting in thefollowing optimization problem

$\min\limits_{W}\{ {{- {\sum\limits_{i = 1}^{m}{\int{{f( s_{i} )}\log\mspace{11mu}{f( s_{i} )}{\mathbb{d}s_{i}}}}}} + {\int{{f(s)}\log\mspace{11mu}{f(s)}{\mathbb{d}s}}}} \}$

All preceding cost function optimizations having an integral form may beimplemented using summations by approximating the underlying pdf's withdiscrete pdf's, for example as the result of estimating the pdf usingwell-known histogram methods. We note that knowledge of the pdf, or evenan estimate of the pdf, may be difficult to implement in practice dueeither to computational complexity, sparseness of available data, orboth. These difficulties may be addressed using cost functionoptimization methods based upon kurtosis, a statistical parameter thatdoes not require a pdf.

In an alternative method a measure of independence could be expressedvia kurtosis, equivalent to the fourth-order statistic defined as thefollowing for the i^(th) component of skurt(s _(i))=E{s _(i) ⁴}−3(E{s _(i) ²})²

In this case W is found as a matrix that maximizes kurtosis of s=Wy overall the components of s (understanding y to be a vector of randomvariables corresponding to the components of y(t)). In all the previousexamples of ICA optimization the solution W could be found via numericalmethods such as steepest descent, Newton iteration, etc., well known andestablished in the art. These methods could prove numerically intensiveto implement in practice, particularly if many estimates of statisticsin s must be computed for every iteration in W.

Computational complexity may be addressed several ways. To begin, theICA could be performed on the PCA-separated signal ŷ(t) with thedimensionality reduced to only the first few (or in the simplest case,two) principal components. For situations where two principal componentsare not sufficient to separate the sources, the ICA could still beperformed pairwise on two components at a time, substituting componentpairs at each iteration of W (or group of iterations of W).

In one example, a simplified two-dimensional ICA may be performed on thePCA separated signals. In this case, a unitary transformation could befound as a Givens rotation matrix with rotation angle θ,

${W(\theta)} = \begin{pmatrix}{\cos\mspace{11mu}\theta} & {\sin\mspace{11mu}\theta} \\{{- \sin}\mspace{11mu}\theta} & {\cos\mspace{11mu}\theta}\end{pmatrix}$where s(t)=W(θ)y(t). Here W(θ) maximizes the probability distribution ofeach component along the basis vectors, such that the following issatisfied.

$\theta = {\arg{\max\limits_{\theta}{\sum\limits_{t = 1}^{T}{\log\mspace{11mu}{f( {s(t)} \middle| \theta )}}}}}$

This optimal rotation angle may be found by representing vectors y(t)and s(t) as complex variables in the polar coordinate formy=y₁+iy₂=ρe^(iφ), s=s₁+is₂=ρe^(iφ′) and finding the relationshipsbetween their angles φ,φ′:φ=φ′+θ, where θ is the rotation that relatesthe vectors. Then, the angle θξ=e ^(i4θ) E(ρ⁴ e ^(i4φ′))=e ^(i4θ) E[(s ₁ +is ₂)⁴ ]=e ^(i4θ)(κ₄₀^(s)+η₀₄ ^(s))may be found from the fourth order-statistic of a complex variable ξ,where κ^(s) is kurtosis of the signal s(t).

By definition, source kurtosis is unknown, but may be found based on thefact that the amplitude of the source signal and mixed signals are thesame.As a result,4θ={circumflex over (ξ)}sign(ŷ)

-   -   with γ=E[σ⁴]−8=κ₄₀ ^(s)+κ₀₄ ^(s) and ρ²=s₁ ²+s₂ ²=y₁ ²+y₂ ²

In summary, the rotation angle may be estimated as:

$\theta = {\frac{1}{4}{{angle}( {\hat{\xi}\mspace{11mu}{{sign}( \hat{\gamma} )}} )}}$where${\hat{\xi} = {{\frac{1}{T}{\sum\limits_{{t = 1},T}{\rho_{t}^{4}{\mathbb{e}}^{{\mathbb{i}4\varphi}{(t)}}}}} = {\frac{1}{T}{\sum\limits_{{t = 1},T}( {{y_{1}(t)} + {{\mathbb{i}}\;{y_{2}(t)}}} )^{4}}}}},{\hat{\gamma} = {{{\frac{1}{T}{\sum\limits_{{t = 1},T}\rho_{t}^{4}}} - 8} = {{\frac{1}{T}{\sum\limits_{{t = 1},T}( {{y_{1}^{2}(t)} + {{\mathbb{i}}\;{y_{2}^{2}(t)}}} )^{4}}} - 8}}}$

After the pre-processing step, the cardiac signal is normally the firstor second most powerful signal. In addition, there is usually inpractice only one source signal that is temporally white. In this case,rotation of the two-dimensional vector y=y₁+iy₂=ρe^(iφ) is all that isrequired. In the event that more than two signals need to be separated,the Independent Component Analysis process may be repeated in pair-wisefashion over the m(m−1)/2 signal pairs until convergence is reached,usually taking about (1+√{square root over (m)}) iterations.

A PIMD that implements the above-described processes may robustlyseparate the cardiac signal from a low SNR signal recorded from theimplantable device. Such a PIMD robustly separates cardiac signals fromnoise to allow for improved sensing of cardiac rhythms and arrhythmias.

The system operates by finding a combination of the spatially collectedlow SNR signals that makes cardiac signal and noise orthogonal to eachother (independent). This combination achieves relatively cleanextraction of the cardiac signal even from negative SNR conditions.

A PIMD may operate in a batch mode or adaptively, allowing for on-lineor off-line implementation. To save power, the system may include theoption for a hierarchical decision-making routine that uses algorithmsknown in the art for identifying presence of arrhythmias or noise in thecollected signal and initiating the methods of the present invention.

Various modifications and additions can be made to the preferredembodiments discussed hereinabove without departing from the scope ofthe present invention.

Accordingly, the scope of the present invention should not be limited bythe particular embodiments described above, but should be defined onlyby the claims set forth below and equivalents thereof.

1. A processor-implemented method, comprising: sensing a plurality ofcomposite cardiac signals over time at a plurality of patient-internallocations; performing a plurality of source separations using sensedcomposite cardiac signals over time; producing a cardiac signal vectorindicative of a cardiac activation sequence of an area of the patient'sheart based on each of the plurality of source separations; monitoring acharacteristic of the cardiac signal vectors relative to a baselineestablished for the characteristic; detecting a change in thecharacteristic relative to the baseline; and identifying an anomalouscardiac condition based on the detected change; wherein the processorimplements at least some of the method.
 2. The method according to claim1, wherein performing at least some of the plurality of sourceseparations is initiated periodically or in response to occurrence of apredetermined event.
 3. The method according to claim 1, whereinperforming at least some of the plurality of source separations isinitiated manually.
 4. The method according to claim 1, whereinperforming at least some of the plurality of source separations isinitiated in response to a change in a therapy delivered to the patientor a change in patient posture.
 5. The method according to claim 1,comprising establishing the baseline of the cardiac signal vectorcharacteristic by performing an initial source separation using sensedcomposite cardiac signals.
 6. The method according to claim 1,comprising establishing the baseline of the cardiac signal vectorcharacteristic using clinical data.
 7. The method according to claim 1,comprising tracking changes of the cardiac signal vector characteristicrelative to the baseline over time.
 8. The method according to claim 1,comprising tracking acute and chronic changes of the cardiac signalvector characteristic relative to the baseline over time.
 9. The methodaccording to claim 1, comprising trending changes of the cardiac signalvector characteristic relative to the baseline over time.
 10. The methodaccording to claim 1, comprising one or more of initiating, adjusting,optimizing, and terminating therapy delivery to the patient in responseto detecting the change in the characteristic relative to the baseline.11. The method according to claim 1, wherein the cardiac activationsequence comprises one or both of a cardiac depolarization sequence anda cardiac repolarization sequence.
 12. An apparatus, comprising: aplurality of implantable electrodes configured for sensing compositecardiac signals over time; a housing configured for implantation in apatient; and a processor provided in the housing and coupled to theplurality of implantable electrodes, the processor configured to performa plurality of source separations using sensed composite cardiac signalsover time, produce a cardiac signal vector indicative of a cardiacactivation sequence of an area of the patient's heart based on each ofthe plurality of source separations, monitor a characteristic of thecardiac signal vectors relative to a baseline established for thecharacteristic, detect a change in the characteristic relative to thebaseline, and identify an anomalous cardiac condition based on thedetected change.
 13. The apparatus according to claim 12, wherein theprocessor is configured to perform at least some of the plurality ofsource separations periodically or in response to occurrence of apredetermined event.
 14. The apparatus according to claim 12, whereinthe processor is configured to perform at least some of the plurality ofsource separations in response to a manually initiated command.
 15. Theapparatus according to claim 12, wherein the processor is configured toperform at least some of the plurality of source separations in responseto a change in a therapy delivered to the patient or a change in patientposture.
 16. The apparatus according to claim 12, wherein the processoris configured to establish the baseline of the cardiac signal vectorcharacteristic by performing an initial source separation using sensedcomposite cardiac signals.
 17. The apparatus according to claim 12,wherein the processor is configured to track changes of the cardiacsignal vector characteristic relative to the baseline over time.
 18. Theapparatus according to claim 12, wherein the processor is configured totrend changes of the cardiac signal vector characteristic relative tothe baseline over time.
 19. The apparatus according to claim 12, whereinthe processor is configured to control one or more of initiating,adjusting, optimizing, and terminating therapy delivery to the patientin response to detecting the change in the characteristic relative tothe baseline.
 20. The apparatus according to claim 12, wherein thecardiac activation sequence comprises one or both of a cardiacdepolarization sequence and a cardiac repolarization sequence.